In sub-Saharan Africa, sustainable intensification of fruit production is affected by pests that strongly impact food and nutrition security. The invasive fruit fly, Bactrocera dorsalis, is a permanent threat to fruit crops, particularly mango. Direct loss is caused by larval feeding in the fruit, but significant indirect loss results when market opportunities are inaccessible due to quarantine restrictions. Another key pest is anthracnose, the most serious disease of mango worldwide. The combined effect of these pests threatens the sustainability of mango production systems, as current pest control methods are insufficient to minimize crop losses. Main objectives of the present project include (i) developing transformative pest control based on the use of insects as smart and reliable conveyors of biopesticides (entomovectoring), and (ii) co-designing with stakeholders biocontrol strategies as part of an integrated pest management framework. High-quality basic and applied research including lab and semi-field tests and small-scale field trials will be performed in Senegal and Kenya to optimize the interactions between insect conveyors (particularly sterile male fruit flies), entomopathogens, and target pests, assess environmental risk, and co-design pilot implementation with stakeholders. Expected results include the design of a two-in-one technology to control mango fruit flies and anthracnose. A key innovation of the project is the coordinated, preventive and area-wide approach, which ensures that all habitats of the target pest are treated, thus limiting re-invasion, as opposed to conventional strategies that focus on independent and often reactive grower interventions at the orchard scale. Our goal is to bring together researchers and stakeholders, to design affordable and environmentally-friendly integrated pest biocontrol, conserve biodiversity, and increase fruit production, rural incomes and employment.

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.

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.

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 ...

Formal Concept Analysis (FCA) is a mathematical framework based on lattice theory and aimed at data analysis and classification. FCA, which is closely related to pattern mining in knowledge discovery (KD), can be used for data mining purposes in many application domains, e.g. life sciences and linked data. Moreover, FCA is human-centered and provides means for visualization and interaction with data and patterns. Actually it is now possible to deal with complex data such as intervals, sequences, trajectories, trees, and graphs. Research in FCA is dynamic, but there is still room for extensions of the original formalism. Many theoretical and practical challenges remain. Actually there does not exist any consensual platform offering the necessary components for analyzing real-life data. This is precisely the objective of the SmartFCA project to develop the theory and practice of FCA and its extensions, to make the related components inter-operable, and to implement a usable and consensual platform offering the necessary services and workflows for KD. In particular, for satisfying in the best way the needs of experts in many application domains, SmartFCa will offer a ``Knowledge as a Service'' (KaaS) component for making domain knowledge operable and reusable on demand.