LEGU-MED: Developing Biodiversity-Based Agriculture with Legume Cropping Systems in the Mediterranean Basin

Environmental degradation and the decrease of ecosystem service provision are currently of major concern, with current agricultural systems being a major driver. To meet our future environmental and sustainability targets a transformation of the agro-food systems and current agricultural value chain are crucial. One approach to redesign farming systems is the concept of biodiversity-based agriculture (BBA) which relies on sustainable diversification of biological components and their natural interactions in farming systems to maximize fertility, productivity, and resilience to external perturbations. Despite minimizing anthropogenic inputs, BBA is not yet able to meet all beneficial environmental objectives. BBA applied in the Mediterranean basin requires urgent innovation in approaches, methodologies, and models for small-holder traditional farming systems to ensure a stable provision of ecosystem services and better resilience to environmental stresses linked to climate change. Legumes are the backbone of the Mediterranean agro-ecosystems from ancient times, but their unique and wide biodiversity was not sufficiently valorized, especially by North-African countries. Here, we present LEGU-MED, a three-year international project funded by PRIMA initiative 2019. An international consortium was established involving five universities, 5 research institutes, and one private company from 8 countries: Italy, Germany, Spain, Algeria, Tunisia, Turkey, Lebanon, and Croatia. The main objective of this project is to put forward an international and well-integrated plan to valorize the legume agrobiodiversity of the Mediterranean in biodiversity-based farming systems and consequently enhance agro-ecosystem functions and services in the Mediterranean basin. The successful completion of LEGU-MED will have the following impacts on Mediterranean legume-based farming systems: (1) improve water use efficiency, (2) reduce the use of anthropogenic inputs through the maintenance of soil fertility, (3) enhance pollination and improve ecological connectivity with flora and fauna, (4) protect close-by wildland ecosystems, (5) enhance other ecosystem services (e.g., pest, disease, and weed suppression), and (6) provide healthier and safer protein-rich food. © 2022 by the authors. Licensee MDPI, Basel, Switzerland

Negation for Free!

Global constraint design is a key success of CP for solving hard combinatorial problems. Many works suggest that automaton-based definitions and filtering make easier the design of new global constraints. In this paper, from such a design, we present an approach that gives an automaton-based definition of the NEGATION of a global constraint... for free! For a given global constraint C, the idea lies in giving operators for computing an automaton that recognizes only tuples that are not solution of C, and use the REGULAR global constraint to automatically reason on this automaton. We implemented this approach for automaton-based global constraints, including global contiguity and lex constraints, and got experimental results that show that their automatically computed negation is highly competitive with more syntactic transformations.Les contraintes globales représentent en grande partie la puissance de la PPC. Ces dernières années, on retrouve de nouvelles représentations des contraintes globales par des automates à état fini (DFA) ou encore des MDD (Multivalued Decision Diagram) avec du filtrage générique. Dans cet article, à partir d'une représentation DFA, nous présentons une approche pour la négation des contraintes globales. En prenant une contrainte globale C, l'idée est de définir des opérateurs qui calculent un automate qui ne reconnait que les solutions de $\neg C$. Pour le filtrage, nous utilisons la contrainte générique REGULAR qui prend l'automate de la version niée de la contrainte. Nous avons expérimenté cette approche sur deux exemples (i.e., global_contiguity et Lex), les résultats sont comparés à ceux d'une négation naïve d'un niveau syntaxique