DigitAF Deliverable 2.5: Plan for improvement of existing tools/models for tree and crop productivity
Creators: name: Gosme, Marie
Publisher: name: Zenodo
Year: 2024

description: Marie Gosme  (1) ,  Tom De Swaef  (2) ,  Christian Dupraz  (3) ,  Marc Jaeger  (4) ,  Karen Lammoglia  (1) ,  Maryline Laurans  (5) ,  Isabelle Lecomte  (1) ,  Magali Pellissier  (6) ,  Benoit Ricci  (1) ,  Clément Rigal  (1) ,  Victor Rolo  (7) ,  Marc Saudreau  (8) ,  Nathalie Smits  (1) ,  Alexia Stokes  (9) ,  François Warlop  (10)

1  UMR ABSys - Agrosystèmes Biodiversifiés  2  ILVO - Research Institute for Agricultural, Fisheries and Food  3  UMR ABSys - Agrosystèmes Biodiversifiés  4  UMR AMAP - Botanique et Modélisation de l'Architecture des Plantes et des Végétations  5  Cirad - Centre de Coopération Internationale en Recherche Agronomique pour le Développement  6  ITEIPMAI - Institut Technique Interprofessionnel des Plantes à Parfum Médicinales et Aromatiques  7  UEX - Universidad de Extremadura - University of Extremadura  8  PIAF - Laboratoire de Physique et Physiologie Intégratives de l’Arbre en environnement Fluctuant  9  UMR AMAP - BotAnique et BioinforMatique de l'Architecture des Plantes  10  GRAB - Groupe de Recherche en Agriculture Biologique

The DigitAF research project (July 2022 - June 2026), funded by the European Commission, aims at a high quality implementation of agroforestry to foster climate change mitigation and adaptation in agriculture and to ensure sustainable management of natural resources. Our goal is to provide stakeholders with tools answering their needs, in particular digital tools. This report presents our plans for improving existing tools and models used to predict tree and/or crop productivity (and potentially other performance indicators) in different conditions of soil, climate (including climate change), type of system, management, etc. . The envisioned improvements fall into 2 categories: - Improving the reliability of the models and tools to fulfil adequately the practitioner’s needs identified in the surveys performed in the Living Labs. This requires including new formalisms to represent e.g. management options that the practitioners wish to compare, or adapting or testing models/tools to new conditions. - Improving the FAIRness score of models and tools, according to the FAIRness criteria developed in WP4. Particular focus has been put on interoperability, because the models were developed somewhat independently, often several years ago and did not have a web 2.0/3.0 concept in mind. Therefore, there are limited data sharing standards to describe AFS and allow interoperability between the different models and tools. This results in duplicate data entries, difficulties for using outputs of one model as inputs for another one, and the impossibility to reuse modules of one model in new models. Another important aspect that we’ll focus on is improving the usability of tools, based on feedback from the stakeholders in the Living Labs. Tools adapted/developed during the project will serve as demonstration vectors for engagement towards the FAIR principles to boost their usage and applicability between peers (other researchers, students, etc.) and downstream marketable applied tools.