Forests are a major reservoir of biodiversity and trees, as keystone organisms, directly impact the diversity and functioning of forest communities. Predicting the response of trees to ongoing global change (GC) is thus a critical scientific and societal issue. Along with phenotypic plasticity and migration, genetic adaptation is a central component of this response, particularly in trees whose high levels of diversity and long distance gene flow facilitates the spread of favorable genes. However, the existence of abundant genetic variation does not guarantee adaptation: if the climate and environmental changes are too quick, or genetic modifications are too slow, the population would go extinct before it can adapt to the new environmental challenges. Our hypothesis is that there is a critical level of genetic diversity for stress responses, which, together with the demographic impact of stress, predicts the likelihood of adaptation or extinction. The main goal of TipTree is to identify tipping points in the demographic and micro-evolutionary dynamics of tree populations, and to assess how human actions interfere in the adjustment between the rate of evolution and the velocity of GC. TipTree benefits from the BiodivERsA project LinkTree (2009-2012) which investigates the evolutionary response of key forest tree species to GC by analyzing the spatial variation of stress tolerance candidate genes along environmental gradients. But TipTree brings a new and critical dimension, that of time, by focusing on regeneration. In trees, regeneration (from fertilization to early plant recruitment) is a key period of the life cycle, when selection is expected to be very strong and has the potential to catalyze the rapid spread of evolutionary novelties in the next generation. The amount of genetic variation available in adults and how it is transmitted, selected and expressed in juveniles will condition the ecological properties of the whole ecosystem in the next decades to centuries, which remains a challenging short and non-equilibrium term of evolution for long-lived organisms. Specifically, our consortium will: 1) Screen the ecological and geographical margins of widespread keystone forest trees from different ecoregions (Temperate, Boreal, Mediterranean and Tropical) to identify where recent environmental changes have provoked shifts in allele frequencies at adaptive genes and to quantify these shifts by contrasting parent and offspring genetic and phenotypic compositions. We will address key environmental drivers: water stress, temperature regime, storm/fire frequency, pest outbreaks. Using natural and controlled (reciprocal transplants, common gardens) populations from existing Pan-European networks, we will generate large arrays of genomic polymorphisms using innovative genomic approaches, 2) Test the existence and evaluate the magnitude of tipping points for tree population dynamics at micro-evolutionary scales, by using a new generation of models coupling biophysics, population dynamics and quantitative genetics. We will feed these models with (i) climate change scenarios provided by IPCC, (ii) forest management scenarios established by our stakeholder group and (iii) our experimental results on adaptive genetic diversity. Micro-evolution of tree populations will be simulated at local and regional scales, and will provide forecasts of ecosystem services (carbon budget and water balance) and decision support for management.

Current Earth Observation systems provide operational tools to derive areal evapotranspiration (ET) for drought monitoring and sustainable management of agricultural water. But partitioning ET into transpiration T and evaporation E is also key for targeting plant water use efficiency and plant water stress conditions at landscape scale. T and E are estimated through land surface models (LSM) forced by visible/near infrared and thermal infrared (TIR) remote sensing (RS) data. However, water budget-based LSM face parameterization issues to constrain water limited T and E rates, while dual-source energy budget-based LSM forced by TIR observations provide separate estimates of T and E, but rely on specific assumptions to retrieve both components from a single composite surface temperature. Additional information is thus required, either specifically related to E (surface water content, cf. Sentinel-1 S1) or T (Shortwave infrared SWIR, cf. Sentinel-2). HiDRATE aims at determining how the existing and future (TRISHNA, LSTM) TIR observations can map T and E by synergistic use of RS observations of multiple wavelengths in conjunctions with LSMs of various complexities. This includes the directional RS signature in terms of soil and canopy cover fraction in the sensor field-of-view. The relevance of increasing modeling complexity or the number of RS constraints in inferring T and E will be assessed using in-situ experiments at local scale including independent ET, E/T, T and E estimates based on eddy covariance, lysimeters, sap flow and stable isotope measurements for several biomes and climates. Drone campaigns will be organized to mimic the revisit cycle of the future satellites. HiDRATE builds on the complementarity of two groups who share expertise in TIR ET retrieval: on the French side, experts in E+T measurements/modeling, as well as soil moisture mapping from S1; on the Luxembourg side, experts in airborne mapping as well as plant water stress assessment using SWIR.

The DIGAP project confronts a problem observed in the field not only by its project leader, but also by Malagasy partners and humanitarian actors: the difficulty of anticipating humanitarian crisis situations linked to droughts. DIGAP argues that a consideration of groundwater status is crucial to anticipating water scarcity-related humanitarian crises in semi-arid regions that are almost devoid of surface water. In fact for some years environmental markers have provided scientific evidence on the hydric situation (e.g. rainfall deficit, drop in piezometric levels). We seek to determine how we can better use water status and more specifically groundwater status, in anticipating humanitarian crises. First (WP1), we will develop an innovative methodology based on remote sensing and modeling to characterize groundwater dynamics at the regional scale in an area that lacks basic documentation. Second (WP2), we will quantify the associations among various environmental factors and food security, in addition to human health indicators through the use of a multi-level epidemiological modeling approach. We expect that our results will unravel the effects of environmental and anthropic factors in the development of drought-related humanitarian crises and thereby sustainably strengthen Madagascar's early warning system.

Even if greenhouse gas emissions decrease in the next decades, rapid change in temperature and rainfall will occur, with long-term implications for the viability of ecosystems and their services. A major scientific challenge is thus to predict the adaptation of natural populations to this changing world in terms of migration, plasticity, and genetic change. Models predicting explicitly the impacts of climate change on biodiversity rarely incorporate any of these mechanisms of adaptation. In this project, we aim at studying the interplay of the three above mechanisms to describe and forecast adaptation of forest trees to climate change. More specifically, we want to (1) evaluate the adaptive value of phenotypic plasticity in current and future climates at different spatial and temporal scales, (2) understand how microevolution in interaction with phenotypic plasticity and gene flow shape phenotypic variation, as well as predict how these three mechanisms of adaptation would act on phenotypic variation in the future, (3) use our increased understanding of phenotypic variation in time and space and its dynamics to better predict current and future species distribution under several scenarios of climate change. Due to their life cycle characterized by long lifetime and large gene flow, forest trees are particularly exposed to temporal and spatial variation in selection. Plasticity may thus play a key role in forest trees response to climate change. The interplay between phenotypic plasticity, microevolution and gene flow on adaptation will be illustrated through the study of phenological traits in three forest tree species, beech, sessile oak and silver fir. Phenological traits have indeed been shown to be a major determinant of tree species distribution and ecosystem functioning. They also show strong responses to current climate change and large genetic variation both within and among populations, suggesting that they might evolve fast if climate change generates new selection pressures. We will focus on bud burst, taking advantage of well-adjusted process-based phenological models predicting its date of occurrence as a function of temperature and photoperiod. The originality of our project lies in (i) integrating different adaptation mechanisms in ecological forecasts of climate change, which has only rarely been attempted; (ii) studying the interaction between these different mechanisms of adaptation, (iii) combining different types of modeling approaches and observations to both explore and predict the adaptive challenges and responses of tree populations experiencing climate changes. More precisely, we will make an original use of extant process-based models simulating variation in bud burst date and its impact on demographic rates, to quantitatively predict the direction and force of selection acting on phenological traits across environments in current and future climate. We will then incorporate this refined understanding of selection pressures in realistic ecological scenarios in quantitative genetics models of variable complexity to predict the joint changes in phenotypic and genetic values for bud burst dates. These predictions will be derived for a set of locations where the genetic and plastic variation in bud burst date are intensively studied, allowing quantitative tests of our predictions, as a validation step. To reach such objectives, our consortium gathers both modelers and experimentalists with complementary expertise in ecology, ecophysiology, quantitative genetics and evolutionary biology. The level of integration among the different tasks is very high. Results will (i) provide answers to fundamental questions about the evolution and adaptive value of phenotypic plasticity in variable environments, (ii) scenarios of range shift of forest tree species integrating adaptation processes and (iii) recommendations for forestry practices to manage the adaptive potential of forest tree species.

FORCES aims towards establishing an evidence-based nature-based solutions (NbS) framework by implementing innovative forest-based solutions. FORCES seeks to develop ecosystem-based adaptation actions that simultaneously preserve high levels of biodiversity, ensure sustaining natural capital and the flow of ecosystem services while protecting communities’ livelihoods and contributing to climate change mitigation. Considering that combined actions on climate, biodiversity and societal challenges cannot efficiently be achieved without multiple actors’ engagement in local actions, FORCES’s strategy is to develop local innovation actions, provide methods and tools to support their extended use and assess their potential global impacts. Thus, FORCES will: i) conduce trans-disciplinary research based on new developments in environmental and social sciences underpinned by stakeholders’ expertise; ii) design, implement and assess local innovation actions based on stakeholders’ engagement; iii) address cross-scale issues from local actions to global impacts; iv) elaborate a tool box of science-based methodologies and standards to promote the use of nature-based solutions that contribute to achieving specific UN sustainable development goals, combining SDG13 “Climate action” and SDG15 “Life on land”, and address societal challenges. FORCES will develop research and innovation actions in various types of forest socio-ecosystems, aiming to generalize forest-based solutions, and will interact with similar projects on other ecosystems through a clustering approach as mentioned in the call. Forests are appropriate for this research and innovation action because: (1) forests harbor an important terrestrial biodiversity and are particularly vulnerable to climate change due to cumulative effects of annual climate on trees, (2) forests are social-ecological systems providing multiple ecosystem services and contributing to people welfare, they are a lever for C-sequestration and substitution, (3) in the context of global change and multiple uncertainties, the emergence of a new paradigm in forest management offers opportunities to innovate, (4) forests are at the cross-road of multiple EU policies but biodiversity and climate objectives are not yet considered jointly in forest policies and strategies. NbS will be designed and assessed in six types of forest systems in Europe and the CELAC. These Innovation Action Areas will be supported by associated Research Sites for data acquisition and model calibration. Multiple time frames will be considered to account for uncertainties in global change scenarios (2035, 2050, 2100).