In a rapidly changing world, we need operational tools to predict and manage responses of biodiversity. To date, although it is clear from both theoretical and empirical work that adaptation can influence the persistence of populations on short time scales, biodiversity scenarios are conspicuously lacking an evolutionary component. One major limitation to the implementation of scenarios including adaptation dynamics is that our knowledge of evolutionary potential and constraints is still too imperfect. In this project, we propose to improve our understanding of adaptive mechanisms in wild populations by integrating theoretical and empirical approaches in wild bird populations at different spatial and taxonomic scales. Using state of the art molecular and quantitative genetics tools in combination with demographic analysis, we will use several populations / species of birds studied in the long-term to identify i) forces of selection acting on natural populations, and especially forces driven by climate change, ii) environmental factors affecting dispersal rates, with a special interest for habitat structure and fragmentation, iii) ecological and phylogenetic factors shaping genetic architecture and affecting its stability, and iv) which regions of the genome show signatures of selection and are therefore likely to be partially responsible for adaptation to different environments. Using a comparative approach among populations and species will allow investigating evolutionary processes at different time and space scales and hence link micro and macroevolutionary patterns. These results will be included in predictive niche models that will assess to which extent the inclusion of rapid evolution and stability of evolutionary potential are affecting predictions from biodiversity scenarios. Hence our approach should provide new tools at the interplay of ecology and evolutionary biology to quantify to what extent model projections neglecting the adaptive component might bias estimates of species extinction risks which are key parameters for policymakers. Moreover, we will put great emphasis on communicating the importance of the biodiversity/evolution interface by (i) collaborating with policy-makers working on biodiversity within the Food and Agricultural Organisation of the United Nations and by (ii) strengthening citizen science through the organisation of exhibitions and conferences in a leading natural history museum (Museum d’Histoire Naturelle, Paris). All in all, results from this project will provide an integrative picture of factors affecting responses to global change improving fundamental knowledge at the interface of ecology and evolution but also including a resolutely operational dimension.

Global changes are affecting biodiversity on unprecedented rate and scale with some forecasts suggesting that half of all species could go extinct by 2050. Yet it remains unclear if we can reliably predict the impact of global changes on biodiversity because we lack sufficient understanding of the potential of species to adapt to new environmental conditions. Our objective is to provide the theoretical and empirical foundation to derive species adaptive potential from macroevolutionary patterns. Recent studies using vertebrates and plants as model organisms have revealed that this potential is constrained by their evolutionary history. However, the bulk of Earth’s diversity is invertebrates, among which insects are the most diversified terrestrial organisms; they encompass a considerable variety of forms and life histories and they account for many ecosystem services and disservices. Yet, their evolution – occurring under different constraints than plants or vertebrates – is at best only partly understood. In particular, the spatial and temporal understanding of the diversification in diverse and globally distributed insect groups is conspicuously absent. We have identified a group of phytophagous insects – Saturniidae and Sphingidae, two sister families of moths – that represent an unparalleled insect model for the study of diversification and for the prediction of adaptive potential. This group is unique among insects in being thoroughly documented worldwide and offers an unprecedented opportunity to consider diversity and distribution patterns, as well as macroevolutionary processes, on global scale for all species. Our project proposes: (1) to build a comprehensive species-level phylogeny for the ~4500 species of moths and to conduct the first diversification analysis at global scale in insects accounting for the role of biotic (e.g. dispersal capacity, hostplant range) and abiotic factors (e.g. climate and geological changes); (2) to analyse the evolutionary dynamics of ecological niches and extend existing macroevolutionary models combining phylogenetic, biogeographical, ecological and paleogeological/climatic information; and (3) to test experimentally the ability of these models to predict species responses to environmental changes by analysing in the field species communities of these moths in pristine and human-impacted habitats on three different continents. Our project is designed to bring both empirical and theoretical foundations to the study of species adaptive potential, and it will not only address this topic for the first time on a global scale in a group of invertebrates, but it will also establish, in a more general way and through experimental tests, if and how the evolutionary history of species can be used to forecast species’ responses to contemporaneous environmental changes. This understanding of species fates in the face of global changes is of primary importance at a time when biodiversity loss is recognized as a major societal concern jeopardizing the sustainability of Earth’s eco- and agro-systems in the short term. This study will then contribute to a more rationale formulation of conservation strategies and management in the context of environmental changes.

The responses of animal populations to global change are mediated by proximate behavioral processes that determine the energy budget and, ultimately, the demographic performance of individuals. Animal movement is currently considered as a key behavior for understanding, and so predicting, the responses of animals (such as shifts in spatial distribution) to global change. The plasticity of movement behavior within and among individuals is hence critical to the potential for both adaptive and non-adaptive responses of animal populations to environmental variability and change. Mov-It aims to be among the first empirical based studies to evaluate, at both intra- and inter-specific levels, how individual behavioral heterogeneity impacts movement energetics, habitat selection, and demographic responses to global change. We will (1) quantify intra- and inter-specific variability in movement patterns and activity rhythms and, from this, infer energetic budgets of locomotion in relation to major drivers of global change (temperature, seasonality, landscape modification, human activities) (2) use these new insights to identify population responses to environmental drivers while accounting for individual variability, (3) parametrise spatially explicit demographic models to forecast how population dynamics and distribution should respond to environmental changes and human disturbance, accounting for individual heterogeneity, landscape constraints, and species-specific traits. To reach these goals, we will combine long term monitoring programs on spatial behavior and demography, new empirical data from cutting-edge biologgers, and demographic modeling to generate spatially-explicit demographic models for forecasting population- and species-specific responses to global change. We will focus on large wild herbivores, considered as ecosystem engineers with marked impacts on their habitat, as a highly relevant model group to link fine-scale processes of movement with broad-scale demographic rates and patterns of distribution. We will exploit 6 unique long term monitoring studies (>20 years) of marked individuals (>1000 individuals marked with GPS so far) of 4 species (roe deer, red deer, chamois, mouflon) with contrasting behavior and life histories. We will generate a massive amount of additional, very high resolution, data from GPS monitoring combined with biologgers (200 year-individuals over the 6 sites) to infer ranging behaviors and energetic expenditure. This new generation of biologgers can record tri-axial accelerometry up to 40 times per second, but also geomagnetism, temperature, light, and pressure. They will allow us to obtain completely new insights into animal body micro-movements and behaviors (i.e. proxies of energetic expenditure that previously could only be measured in the laboratory), but also into the local environment experienced by the animal itself in a natural setting. Through 5 linked work packages, we will explore how key dimensions of the landscape which were hitherto beyond the reach of ecological studies (thermal- and energetic-landscapes, WPs 1 & 2), shape movement behavior, time budgets, and energy balance in large herbivores. Next, we will focus on consistent inter-individual variability in movement and activity in relation to habitat heterogeneity, infrastructures (WP3), and human recreational activities (WP4). From there, we will link individual variability in movement and energetic balance to demographic performance by parameterising Integral Population Models (WP5). Mov-It will thereby provide new insights on the sensitivity of population dynamics and spatial distribution of large wild herbivores to forecast global change (both climatic and human-driven) derived from behavioral processes studied at the individual level in species with contrasting life histories, and clearly founded in the principles of evolutionary ecology.

European marginal grasslands are biodiversity hot spots owing to ecological constraints, biophysical heterogeneity, and centuries of agriculture. Currently it is not clear whether these unique systems are vulnerable to ongoing environmental, socio-economic and political changes, or if they have developed a high resilience over their history of co-evolution between humans and ecosystems. In the latter case the limits to this resilience are unknown, and their prediction hazardous. This uncertainty lies largely in the poor knowledge of resilience mechanisms of both the ecological and human sub-systems, as well as those underpinning robustness or vulnerability of the entire system coupled through land management decisions and ecosystem services. REGARDS aims to unravel the mechanisms underpinning resilience of marginal grassland systems to global environmental and social change in order to enhance socio-ecological resilience from farm to regional level. We ask the following questions: (1) Can we identify safe areas vs. tipping points in the combined effects of changing climate, including extremes, and management on grassland ecosystems? (2) How does coupled above-belowground functional diversity buffer or amplify grassland ecosystem responses to combined changes in climate and management? (3) Which landscape structures enhance or decrease ecosystem resilience, and thereby the resilience of ecosystem service provision? (4) Can multi-level governance structures react faster to socioeconomic changes that affect biodiversity and the related ecosystem services? (5) Can system openness, which increases with regional integration and globalization, enhance resilience through its effects on flows of goods and ecosystem services, people and information, or does it threaten a historically resilient system? (6) How can such knowledge support pathways towards increased resilience? REGARDS will address these questions for mountain grassland sites in Austria, France and Norway, where contrasted biophysical and human situations will allow us to explore complementary dimensions of socio-ecological resilience. Questions (1) and (2) will be addressed using an experimental approach combining manipulations of plant functional diversity, climate and management with state-of-the art analyses of soil microbial diversity, transcriptomics, and fluxomics. Remote sensing will be used to quantify landscape functional structure and its role in facilitating or impeding flows of ecosystem services (question 3). Question (4) will be addressed by an assessment of how local, regional, national and EU programs affect farmers responses and resilience in the context of the variety of socio-ecological factors influencing decisions at farm level. Question (5) will be addressed by reconstructing past land uses and exchanges with other regions of each site, and by comparing indicators of socio-ecological resilience through time and across sites. Finally we will build on this mechanistic knowledge (questions 1-5) to address question (6) using a participative scenariobased approach. Scenarios varying openness of the human-environment system and governance structures will be defined with key local and regional stakeholders and decision makers. Evaluation of scenario outcomes in terms of biodiversity, ecosystem services and material well-being, and associated tipping points will be used to foster knowledge building about socio-ecological resilience at farm and local/regional level.