"The major challenge in climate-change ecology is to predict the impact of future climate change on populations. To provide the most realistic way to forecast the future of key species, we must consider simultaneously demographic (e.g. growth, rate of survival and reproduction), physiological/behavioural mechanisms (e.g. hormonal responses, thermal tolerances, huddling) and genetic vs phenotypic variation. However integrative mechanistic population models that incorporate these processes remain scarce. The ARC project meets this challenge and responds today to the need of a complete framework. It will provide a mechanistic view of the causes and consequences of populations’ responses to climate change to predict their distribution and implement accurate conservation strategies. My project presents a rare combination of data, skills and experience by combining a long-term (1990-2012) dataset and experimental explorations of the proximal mechanisms using the Alpine marmot (Marmota marmota) as a model species. Using a four-tier approach, I will (i) investigate environmental and social factors that influence phenotypic and phenological traits affecting population dynamic; (ii) determine the physiological mechanisms underlying the critical trait-demography relationships; (iii) identify the relative roles of evolutionary and ecological responses. Then, I will integrate demographic, physiological and evolutionary processes identified above to predict the change in this alpine species’ range and evaluate its vulnerability or resilience to current climate change.To elucidate the complexity of adaptive responses to climate change, it brings together complementary knowledge and methods from disparate disciplines. The multi-disciplinary approach and state-of-the-art methods proposed by the ARC project is a crucial step towards a more comprehensive and mechanistic understanding of the influence of climate change on population viability and, ultimately, on biodiversity."