The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems

Ioanna Mouratiadou (1, 2, 3) , Nahleen Lemke (1) , Cheng Chen (1) , Ariani Wartenberg (1) , Ralf Bloch (4) , Marco Donat (1) , Thomas Gaiser (5) , Deepak Hanike Basavegowda (6) , Katharina Helming (1, 4) , Seyed Ali Hosseini Yekani (1) , Marcos Krull (1) , Kai Lingemann (7) , Joseph Macpherson (1) , Marvin Melzer (1) , Claas Nendel (1, 8, 9) , Annette Piorr (1) , Mostafa Shaaban (1) , Peter Zander (1) , Cornelia Weltzien (6) , Sonoko Dorothea Bellingrath-Kimura (1)

1 ZALF - Leibniz-Zentrum für Agrarlandschaftsforschung = Leibniz Centre for Agricultural Landscape Research
2 LER - Laboratoire d'Études Rurales
3 Isara
4 HNE - Eberswalde University for Sustainable Development
5 INRES - Institute of Crop Science and Resource Conservation [Bonn]
6 Leibniz Institute for Agricultural Engineering and Bioeconomy (ATB)
7 DFKI - Deutsches Forschungszentrum für Künstliche Intelligenz GmbH = German Research Center for Artificial Intelligence
8 Institut für Chemie [Universität Potsdam] | Institute of Chemistry [University of Potsdam]
9 CzechGlobe - Global Change Research Centre

Multifunctional and diversified agriculture can address diverging pressures and demands by simultaneously enhancing productivity, biodiversity, and the provision of ecosystem services. The use of digital technologies can support this by designing and managing resource-efficient and context-specific agricultural systems. We present the Digital Agricultural Knowledge and Information System (DAKIS) to demonstrate an approach that employs digital technologies to enable decision-making towards diversified and sustainable agriculture. To develop the DAKIS, we specified, together with stakeholders, requirements for a knowledge-based decision-support tool and reviewed the literature to identify limitations in the current generation of tools. The results of the review point towards recurring challenges regarding the consideration of ecosystem services and biodiversity, the capacity to foster communication and cooperation between farmers and other actors, and the ability to link multiple spatiotemporal scales and sustainability levels. To overcome these challenges, the DAKIS provides a digital platform to support farmers' decision-making on land use and management via an integrative spatiotemporally explicit approach that analyses a wide range of data from various sources. The approach integrates remote and in situ sensors, artificial intelligence, modelling, stakeholder-stated demand for biodiversity and ecosystem services, and participatory sustainability impact assessment to address the diverse drivers affecting agricultural land use and management design, including natural and agronomic factors, economic and policy considerations, and socio-cultural preferences and settings. Ultimately, the DAKIS embeds the consideration of ecosystem services, biodiversity, and sustainability into farmers' decision-making and enables learning and progress towards site-adapted small-scale multifunctional and diversified agriculture while simultaneously supporting farmers' objectives and societal demands.

Mots clés: Digital agriculture; Ecosystem services; Decision support system; Farming practices; Biodiversity; Modelling; Small-scale management

Domaines: Sciences de l'environnement

Ioanna Mouratiadou, Nahleen Lemke, Cheng Chen, Ariani Wartenberg, Ralf Bloch, et al.. The Digital Agricultural Knowledge and Information System (DAKIS): Employing digitalisation to encourage diversified and multifunctional agricultural systems. Environmental Science and Ecotechnology, 2023, 16, pp.100274. ⟨10.1016/j.ese.2023.100274⟩. ⟨hal-04079999⟩