Agricultural production will be decisively affected as global climate change continues and water shortage and drought are becoming increasingly serious constraints that limit crop production, not only in Mediterranean area but also worldwide. The project TomorrowS will largely focus on the impact of climate change on cotton (Gossypium hirsutum L) and durum wheat (Triticum durum), two main crops in the Mediterranean region. These crops have a negative environmental impact due to increased use of inputs involved in building resilience to biotic and abiotic stresses. The aim of TomorrowS is the optimization of crop management for these two major Mediterranean crops, in order to adapt them to projected climate change negative impacts. Therefore, TomorrowS will reduce uncertainties on crop yield and will provide supporting information to help farmers managing their crop. In addition, due to uncertainties on irrigation water availability and pesticides costs, TomorrowS will target in cropping systems that are resilient to sub-optimal use of such inputs. Besides the above stated main objectives, this project also aims to provide a generic methodological framework to design sustainable agriculture systems for other crops and countries, and last but not least, promote synergies among young researchers. TomorrowS is a trans-disciplinary project as it requires insights from agronomy, physiology, crop modeling and data management to generate the optimized cropping systems. Three young researchers from Greece, Tunisia and France will exchange knowledge, cooperate and strengthen their scientific capacities thanks to TomorrowS. Cotton, is a major agricultural crop in Greece, accounting for more than 8% of total agricultural output, engaging more than 75,000 farmers while durum wheat is the most cultivated crop in Mediterranean basin, representing the main population diet component for pasta. In Greece, durum wheat covered 16.2% of the total cultivated area and 60% of total production is exported mainly in Italy while in Tunisia, is the primary food source as the consumption reaches 258 kg per year per capita. The dataset will be generated by two years of Genotype x Environment x Crop Management (GEM) experiments conducted in Greece and in Tunisia for 3 to 4 commercial varieties of cotton and durum wheat. The factors studied in the GEM experiments will be the cultivar, amount of fertilization, amount of irrigation and salt content of irrigation water. These GEM experiments will provide sufficient data to calibrate, evaluate and enhance a deterministic crop model embedded in the Decision Support System for Agrotechnology Transfer (DSSAT) software application, which will be accomplished by the French partner. Once, GEM interactions are properly described and calibrated in the model, the model will be used to simulate virtual ideotype of crop management and describe the tradeoff between production, resilience and use of resources along with the uncertainty on production. In addition, economic viability of crop management ideotypes will be evaluated. The results from TomorrowS will be diffused to the scientific community through publications in national and international journals and also with the participation of the consortium members to international conferences and national meetings. Summarizing, this ARIMNET2 project implementation will contribute to the adaptation of cotton (Gossypium hirsutum L) and durum wheat (Triticum durum) crop managements facing constraint such as irrigation water salinity, under the present and the projected future Mediterranean climates. In that context, the results should contribute to (i) increase yield while reducing yield inter-annual variability, (ii) increase economic viability of farms by increasing water and fertilizer use efficiencies.

Crop pests are a major constraint to ecological intensification of agricultural production systems. Integrated Pest Management (IPM) is an ecosystem approach that combines different strategies and practices to minimize the use of pesticides. Its implementation requires a sound knowledge of pest population dynamics and underlying ecological processes to assist decision-making. In particular, the integration of pest dispersal processes (e.g. active and passive, short and long-distance, human-assisted and windborne) that condition seasonal crop infestation, opens up opportunities for preventive interventions (e.g. targeting residual populations) at relevant spatial and functional scales (e.g. the production basin). Accounting for pest dispersal in relation to their environment and at multiple scales is pivotal to a fundamental shift in the contours of action, from conventional and often individual-based interventions at a cultivated field scale, to collective organisation and management at a territory scale. The design of such an IPM strategy, however, also requires the integration of stakeholders to identify the socio-technical lock-ins to innovations. Since demographic studies are challenging to assess pest dispersal at spatial scales relevant for pest management, an alternative is to use an "indirect" approach based on neutral genetic data. In this context, DISLAND proposes to develop and extend a landscape genetics approach to address “dispersal” issues as a prerequisite to improve pest management strategies. Such an approach includes the assessment, in space and time, of the effect of landscape structure and agricultural practices on spatiotemporal pest abundance and active short-distance dispersal, as well as of the role of passive long-distance dispersal through wind and commodity trades on population dynamics. To this aim, we will develop appropriate tools including a cost-effective high-throughput sequencing technique to produce thousands of highly informative genetic markers (SNPs) for thousands of samples, a dedicated database to ensure the storage, traceability and sharing of all data, and a flexible multi-agent simulator to model demo-genetic processes in realistic landscapes. We will implement an intensive demo-genetic monitoring of the pest and acquire a large set of data highly relevant to its ecology and management (landscape structure, habitat quality, relative abundance and agricultural practices) in contrasted production basins (and beyond, at the regional scale). Finally, we will adapt or develop appropriate statistical methods to characterize the relationships between dispersal and the environmental matrix and quantify the spatial and temporal variation of key demographic parameters for pest management (dispersal and population size). This framework will be designed and applied on the Oriental fruit fly, Bactrocera dorsalis, which is an invasive key pest of mango and other fruits in West Africa. The new knowledge on fruit fly dispersal will then be integrated into a spatially-explicit simulation model representing pest population dynamics and interactions with stakeholders. This model will serve as a tool for participatory evaluation and conception of system-wide fruit fly management strategies. This innovative research will bridge agronomy, landscape ecology, population dynamics and population genetics, and socio-ecology.

Biodiversity loss in hotspots of biodiversity is, among other socio-ecological factors, key to understand, prevent and react to future pandemics. However, despite this knowledge, the current COVID-19 crisis highlights the limitations of the implementation of One Health approaches. A main limitation is the lack of context-adapted solutions that stakeholders (national authorities but also local communities, NGOs and private companies) could easily implement on the field. To overcome this, the MARBLES partners will build on past international projects to co-construct innovations with all stakeholders of biodiversity hotspots to reduce the risk of infectious disease emergence through biodiversity conservation and disease surveillance strategies. The activities of the project will be implemented in Europe and three tropical biodiversity hotspots in Southeast Asia, West Africa and Central America and will have the following expected impacts: • the results of the MARBLES project will lead to a better understanding of the mechanisms underlying the impact of biodiversity on the risk of infectious disease emergence • Stakeholder’s engagement tools developed during the MARBLES project will facilitate the design of context-adapted biodiversity conservation and restoration strategies that reduce zoonotic risk • the surveillance strategies and pathogen detection tools developed during the MARBLES project will improve the capacities to detect emergences and stop future epidemics before they can turn into pandemics The consortium will constitute a strong multi-actor group of partners with a history of successful cooperation including academics from biomedical, environmental and social sciences, private companies, NGOs, local and international stakeholders who bring together the wide range of disciplines and expertise required to reach all the expected outcomes of the HORIZON-CL6-2021-BIODIV-01-11 call. Overall, the implementation of the MARBLES project in various ecological, climatic and cultural settings will allow the consortium members to develop generic innovations that could subsequently be adapted through to a wide range of socio-ecological settings, contributing to the understanding, prevention and early detection of zoonotic emerging threats globally. The embedment of the MARBLES project in the Prezode initiative will help to scale up the project innovations and disseminate cutting-edge socio-economic environmental strategies.

The DATA4C + project is part of the open science (RDA) and soil carbon initiatives (4 per 1000 in particular). In order to meet the objectives of these initiatives, there is a great challenge to reference, in databases, not only the analyzes but also the associated metadata and to make databases interoperable. Based on this observation and the leading role played by CIRAD, INRA and IRD at national and international level on the topic of soil carbon, the DATA4C + project has the following objectives: (OS1) Define rules of good practice to describe the data in the soil carbon databases and provide them with consistent information; (OS2) Analyze the computer and legal barriers for interoperability between soil carbon databases and soil management modes in order to propose solutions for alleviating them; (OS3) Experiment with the implementation of methodological solutions formulated by the project in a French overseas department; (OS4) Exchange and disseminate internationally on the project. The results of DATA4C + are intended to be integrated into the practices and tools of CIRAD, INRA and IRD within the framework of their respective strategies relating to digital and open science. Beyond the soil carbon community, the semantics validated in the DATA4C + project will be published / disseminated and will be used by other scientific communities. In addition, solutions / options from the DATA4C + project may also be valid for other soil parameters and then support other teams. In addition, the availability of soil carbon data and metadata will eventually have very different targets: States, engineering offices ...