Recent studies suggest that transgenerational metabolic impairments induced by endocrine disruptors (ED) exposure are key contributing factors in amphibian population decline by altering individual fitness. However, several questions remain to be explored: How do obesogenic EDs act in frogs? What are the crosstalks with other hormonal axes?) Which parent transmits the metabolic disorders to progeny? Are transgenerational metabolic disorders dependent on epigenetic modifications or linked to diminished reserve stores in eggs by females thereby affecting the progeny metabolism? To what extent may delayed life history traits changes in progeny compromise the demographic maintenance of amphibian populations. The Macdonald project will address these questions by studying the effect of a mixture of 6 obesogenic EDs at environmental concentrations over 3 generations of X. tropicalis (F0 exposed and F1/F2 unexposed). The effects of mixture will be evaluated at each generation through growth parameters, reproductive, thyroid and neurodevelopmental effects, metabolic impairments and transgenerational inheritance. Finally, stage-structured population models will be built based on the developmental and reproduction parameters recorded to assess potential demographic impacts of ED exposure.

Early-life conditions have pervasive and far-reaching consequences for the life history of most animals. In long-lived species, many phenotypic traits that are expressed in adulthood depends on the environmental conditions encountered during early life, from early pregnancy to weaning. The developmental history of an organism thus influences the outcome of the interaction with its current environment at each life stage, with extensive implications for population dynamics and the evolution of life histories. Carry-over effects are events, processes or experiences that occur during a given stage of an individual development and that alter the state or condition of the individual in a later stage. Although movement is a key behaviour linking environmental conditions to an individual’s fitness, how early life conditions and its interplay with subsequent events influence movement, and how it relates to phenotype and performance during adulthood remains largely unexplored. CARRY-MOVE will fill this gap by evaluating the roles of early life conditions on the ontogeny of movement, and their carry-over impacts on movement during adulthood and ultimately, on performance. Our central objective is to explore the direct and delayed pathways by which global changes impact the lifetime track of individuals and, in turn, the population dynamics of large herbivores with contrasting life histories. In WP1, using 2 exceptional long term study sites with marked juveniles, we will link early conditions and experience to early and later movements and individual performance. In WP2, we will evaluate the effects of between- and within-cohort variation in early life conditions on adult behaviour and movement using a larger range of species. Finally, using worldwide datasets, we will assess in WP3 whether the response of adult movement tactics to early life conditions varies according to a range of structuring factors known to shape life history variation.

"In the context of the implementation of sustainable solutions for the objectives ""Life on Earth"" (#15), ""Climate Action"" (#13), and ""Sustainable Tourism"" (target 8.9) and in particular to measure human pressures on ecosystems, the aim of the IntForOut project is to develop new methods and tools to build spatio-temporal databases integrating heterogeneous data coming from multiple sources of spatial data: national, regional and local authorities, communities of researchers and citizens (via participatory science or volunteered geographic information). IntForOut will focus on the issue of wildlife disturbance caused by recreational activities in mountains. In this rapidly changing geographical context, multi-source integration will allow knowledge to be shared between researchers from different disciplines, with land managers and with users, which in turn will improve the monitoring of ecosystems on large spatial and temporal scales. The project will propose an approach based on knowledge engineering methods (knowledge graph) to obtain, represent and provide the necessary expertise during the integration process and for the stakeholders managing the ecosystems. The integration process will be based on multi-scale data matching, quality assessment, semantic enrichment, and metadata description. An open knowledge graph and databases for ecosystem monitoring will be available in an ETL open platform. The integration of data will be tested in two pilot cases in the mountains (Bauges and Chamonix Mont-Blanc), with the aim of making these human-wildlife issues visible and proposing mitigation levers to tourism managers, such as raising user awareness via participatory science or calculating resilient routes to destinations."

Abandonment of less productive grasslands in European mountains leads to colonization by shrubs, which climate change is expected to further favour. These changes in plant biodiversity and associated biota profoundly alter grassland biogeochemical functioning and ecosystem services (ES). LUCSES aims to develop understanding of nitrogen (N) and water-cycling processes in shrub-encroached mountain grasslands to support novel trait-based models for predicting global change effects on mountain grasslands. The core hypothesis of LUCSES is that shrub colonization induces a tipping point in relationships between plant economics traits and processes of N- and water-cycling, which can be related to specific shrub traits and to mycorrhizal functions. LUCSES will take significant steps towards reducing limited trait and functional knowledge for mountain shrubs. While a first step has been taken across the cold biome based largely on ‘soft’ traits, LUCSES aims to address more directly functional processes affecting soil N and water dynamics using ‘harder’ traits and considering mycorrhizal associations. In particular, the biochemical nature and functions of alpine shrub secondary compounds are poorly elucidated, due to the technical barriers of their analyses in the field. LUCSES will improve methods for screening large numbers of plant samples and for detecting intraspecific variation in experimental conditions by combining biochemical analysis and IR spectrometry. Functions of mountain shrub mycorrhizae and their responses to critical climate modifications such as early snowmelt and drought have never been described. Seasonal dynamics of N and mycorrhizae remain both a scientific and a technical challenge due to their lability, and functional effects of changes in snow cover are a research frontier. By analyzing at our French and Austrian long-term research sites variation along encroachment gradients of plant traits specific to deciduous vs. evergreen shrubs and mechanisms associated with their mycorrhizae, we will elucidate pathways of effects of combined land use and climate change. We will use lysimeters to analyze full water balance, overcoming the scientific barrier of linking changes of functional traits to water-related ecosystem functions. Resulting structural equation models will be used to develop trait-based ES models, parameterised from field surveys and climate manipulations. ES models application to land use change trajectories from past to present, and to future scenarios will highlight trade-offs and adaptation options from shrub encroachment at our two sites and for the Ecrins National Park (France). The LECA (lead: B. Mouhamadou) and University of Innsbruck (lead: G. Leitinger) teams comprise extensive and complementary scientific and technical expertise, and very experienced staff in all relevant aspects for the project of plant functional ecology, microbial ecology, climate change experiments and ecosystem service modelling. LUCSES results will help building capacity on poorly known, yet inevitable ecosystem transformations and support management and decisions by our socio-economic partners. We thus intend to support medium- and long-term climate change adaptation in mountain regions by providing decision makers and the public with evidence on options from managing ecosystems and landscapes.

High-throughput sequencing of genomes of one or many species living in distinct habitats has opened extraordinary perspectives for predicting species responses to climate change. The objective of this research project is to develop statistical methods for predictive ecological genomics (PEG) based on environmental and genomic DNA. The project focusses on predicting the vulnerability of a species or an assemblage of species by using projections of altered environments. The proposed algorithms are based on modern statistical approaches, including deep latent variable models and approximate Bayesian inference. In collaboration with population geneticists and ecologists, the project will apply the methods to African crops and to Alpine biotopes threatened by global warming. This project will allow us to better understand population and ecological community responses to climate change, target plant cultivars, and assist conservation of key or endangered species.