Conserving biodiversity urgently requires the integration of knowledge across ecological-time, -scales and -disciplines. AA-ungulates will fulfil such major ambition, developing an innovative framework joining palaeoecology to evolutionary demography. By extracting invaluable knowledge from millennia of natural history and detailed demographic data, this project will provide advances in predicting species persistence under rapid global changes. Specifically, the project will study 1) the effect of climate and harvest on effective population sizes of Arctic and Alpine ungulates at historical (using subfossil genomics) and 2) contemporary (using genomics and demography) timescales, to 3) project their population viability under credible climate scenarios. To achieve these novel goals, I propose a pioneering approach linking state-of-the-art genomics from ancient and modern specimens to individual-monitoring programs. To maximize societal impacts, the research focuses on charismatic ungulates sharing histories of hunting-induced bottlenecks and inhabiting biomes warming the fastest on Earth. These unique empirical datasets will allow theoretical advancements by identifying common genetic-to-demography processes, with important insights on how population viability is tied to low genetic diversity. To undertake this integrative endeavor, a two-way transfer of knowledge will be crucial between the Beneficiary (Université Savoie-Mont Blanc, USMB, France) and I. In G. Yannic’s expert group, I will learn about alpine ecology and paleogenomics and in turn will bring knowledge of arctic ecology and demographic biostatistics. A strong collaborative team from 9 institutions in 4 countries, gathering eminent specialists in key aspects of AA-ungulates, will further enrich my network and skills. The high-quality outputs planned, supplemented by the diverse early-career programs at USMB, will give a springboard to become an independent expert in multiscale evolutionary demography.

The analysis and interpretation of geophysical signals and images are used to monitor active volcanoes and determine the presence and characteristics of magma chambers. The signals that are measured and inversed, i.e. seismic wave velocities, densities, electrical resistivities, or ground deformation, depend on rocks temperature, melting degree and volatile content. Those parameters are interdependent and evolve in time as the magma system grows and matures. We propose to numerically simulate the long-term evolution of magmatic systems and model the corresponding geophysical images and signals. Our objective is to determine how the history and maturation of a system affect the geophysical record and to help improving the interpretation of this record. A major challenge encountered by geophysists is the non-uniqueness of solutions in a multiparameter space, in particular the difficulty to distinguish the effect of melts and of volatiles. To tackle this issue, we will develop codes that compute the exsolution of volatiles and the development hydrothermal circulation. The model will be applied to four different volcanoes: Uturuncu (Bolivia), Campi Flegrei (Italy), Merapi (Indonesia), and Krafla (Iceland). The fellowship objective will be reached through the joint efforts of experienced researcher Annen who is an expert in modelling the evolution of magma chambers, supervisor Revil who is an expert in geophysical inversions and hydrothermal systems, and the team of volcano geophysists of Institute of Earth Science at University Savoie Mont-Blanc (France). It will allow Annen to resume her scientific career after a two-year break, doing cutting-edge science in a highly dynamic environment.

This project aims to analyse how Circular Economy (CE) transitions may affect income distribution and welfare across socio-economic groups. With global material use expected to double in 40 years, reliance on material resources for economic growth raises sustainability concerns. CE offers an alternative by promoting resource efficiency, waste reduction, and material reuse, potentially leading to more sustainable economic growth. Despite the growing importance of CE, there remains a critical gap in understanding its distributional effects, particularly its effects on economic inequality and welfare. While some economic models have been developed to assess the effectiveness of CE policies, they overlook the redistributive dimensions of these transitions. This project seeks to fill this gap by developing a Computable General Equilibrium (CGE) model that integrates both welfare and inequality analysis in the context of CE policies. Building on the work of two string of literature: 1) on CGE modeling which investigate redistributive polices and 2) on CGE modeling of the CE, this project will apply state-of-the-art CGE modeling to assess how CE transitions may affect socio-economic groups. It will explore dynamic scenarios of policy interventions, measuring the effects on income distribution, resource use, and overall welfare. The project's objectives include developing a comprehensive CGE model to analyze CE's effects on redistribution, calibrating the model using relevant economic data, and providing policymakers with actionable insights on how to design equitable and efficient CE policies. Ultimately, this project will provide insights into designing policies that balance socio-economic objectives with environmental sustainability. It will contribute to a deeper understanding of how to ensure that the shift towards a CE is not only resource efficient but also socially equitable, minimizing the risks of increased inequality.