The notions of resilience that have emerged in developmental psychology and psychiatry in recent years require systematic rethinking to address the distinctive cultures, geographic and social settings, and histories of adversity of indigenous peoples. In Canada, the overriding social realities of indigenous peoples include their historical rootedness to a specific place (with traditional lands, communities, and transactions with the environment) and the profound displacements caused by colonization and subsequent loss of autonomy, political oppression, and bureaucratic control. We report observations from an ongoing collaborative project on resilience in Inuit, Métis, Mi'kmaq, and Mohawk communities that suggests the value of incorporating indigenous constructs in resilience research. These constructs are expressed through specific stories and metaphors grounded in local culture and language; however, they can be framed more generally in terms of processes that include: regulating emotion and supporting adaptation through relational, ecocentric, and cosmocentric concepts of self and personhood; revisioning collective history in ways that valorize collective identity; revitalizing language and culture as resources for narrative self-fashioning, social positioning, and healing; and renewing individual and collective agency through political activism, empowerment, and reconciliation. Each of these sources of resilience can be understood in dynamic terms as emerging from interactions between individuals, their communities, and the larger regional, national, and global systems that locate and sustain indigenous agency and identity. This social-ecological view of resilience has important implications for mental health promotion, policy, and clinical practice.

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Denitrification is known as an important pathway for nitrate loss in agroecosystems. It is important to estimate denitrification fluxes to close field and watershed N mass balances, determine greenhouse gas emissions (N 2 O), and help constrain estimates of other major N fluxes (e.g., nitrate leaching, mineralization, nitrification). We compared predicted denitrification estimates for a typical corn and soybean agroecosystem on a tile drained Mollisol from five models (DAYCENT, SWAT, EPIC, DRAINMOD-N II and two versions of DNDC, 82a and 82h), after first calibrating each model to crop yields, water flux, and nitrate leaching. Known annual crop yields and daily flux values (water, nitrate-N) for 1993-2006 were provided, along with daily environmental variables (air temperature, precipitation) and soil characteristics. Measured denitrification fluxes were not available. Model output for 1997-2006 was then compared for a range of annual, monthly and daily fluxes. Each model was able to estimate corn and soybean yields accurately, and most did well in estimating riverine water and nitrate-N fluxes (1997-2006 mean measured nitrate-N loss 28 kg N ha -1 year -1 , model range 21-28 kg N ha -1 year -1 ). Monthly patterns in observed riverine nitrate-N flux were generally reflected in model output (r 2 values ranged from 0.51 to 0.76). Nitrogen fluxes that did not have corresponding measurements were quite variable across the models, including 10-year average denitrification estimates, ranging from 3.8 to 21 kg N ha -1 year -1 and substantial variability in simulated soybean N 2 fixation, N harvest, and the change in soil organic N pools. DNDC82a and DAYCENT gave comparatively low estimates of total denitrification flux (3.8 and 5.6 kg N ha -1 year -1 , respectively) with similar patterns controlled primarily by moisture. DNDC82h predicted similar fluxes until 2003, when estimates were abruptly much greater. SWAT and DRAINMOD predicted larger denitrification fluxes (about 17-18 kg N ha -1 year -1 ) with monthly values that were similar. EPIC denitrification was intermediate between all models (11 kg N ha -1 year -1 ). Predicted daily fluxes during a high precipitation year (2002) varied considerably among models regardless of whether the models had comparable annual fluxes for the years. Some models predicted large denitrification fluxes for a few days, whereas others predicted large fluxes persisting for several weeks to months. Modeled denitrification fluxes were controlled mainly by soil moisture status and nitrate available to be denitrified, and the way denitrification in each model responded to moisture status greatly determined the flux. Because denitrification is dependent on the amount of nitrate available at any given time, modeled differences in other components of the N cycle (e.g., N 2 fixation, N harvest, change in soil N storage) no doubt led to differences in predicted denitrification. Model comparisons suggest our ability to accurately predict denitrification fluxes (without known values) from the dominant...

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