• Title: "Development of a decision support tool to optimize the grazing of spontaneous vegetation based on a functional classification of pastoral resources," Institut Agro Montpellier & AgroParisTech;
  • Doctoral candidate: Elisa Deschamps;
  • Affiliated unit: INRAE, SELMET (Systèmes d’élevage méditerranéens et tropicaux);
  • Co-supervisors:
    • Magali Jouven, Institut Agro Montpellier, SELMET (Systèmes d’élevage méditerranéens et tropicaux);
    • Lucile Sautot, AgroParisTech, TETIS (Information Spatiale au service des Territoires et de l'Environnement);
  • Doctoral School: GAIA, Université de Montpellier.

Grazing spontaneous vegetation is associated with numerous challenges (agroecology, climate change, biodiversity, ...), yet it remains marginal because its value for livestock feeding is poorly understood. The objective of the thesis is to lay the groundwork for a tool to characterize pastoral resources in a specific context in order to optimize grazing management and supplementation. To achieve this, three approaches will be combined: (1) initially, Near-Infrared Spectroscopy (SPIR) on fresh samples, coupled with observations of feeding behavior, will be used to build a database of grazed forage and classify them based on their function in the diet; (2) this classification will be compared with the perceptions of farmers and herders to harmonize scientific knowledge with local knowledge; (3) these two types of knowledge will be used to develop a decision support tool that provides a simple and shared representation of pastoral resources, which can facilitate discussions and decision-making for a variety of stakeholders in pastoralism. The aim is to harness digital technology to produce scientific knowledge that can be linked to local knowledge, making it operational for decision support and the development of economically efficient and self-sustaining systems.