Exploring complementarities between modelling approaches that enable upscaling from plant community functioning to ecosystem services as a way to support agroecological transition. Issue 1 (4th December 2021)

• Record Type: Journal Article
• Authors: Gaudio, Noémie; Louarn, Gaëtan; Barillot, Romain; Meunier, Clémentine; Vezy, Rémi; Launay, Marie
• Editors: Chen, Tsu-Wei; Long, Stephen P; Chen, Tsu-Wei
• Is Part Of: In silico plants. Volume 4:Issue 1(2022)
• Publication Date: 2021-12-04
• Subjects: Crop mixtures -- crop models -- individual-based models -- modelling synergies -- pest regulation -- process-based models; Plant physiology -- Periodicals; Botany -- Periodicals; Botany -- Mathematical models -- Periodicals; Crop science -- Periodicals; 580
• DOI: 10.1093/insilicoplants/diab037
• Languages: English
• ISSNs: 2517-5025

Abstract

Abstract: Promoting plant diversity through crop mixtures is a mainstay of the agroecological transition. Modelling this transition requires considering both plant–plant interactions and plants' interactions with abiotic and biotic environments. Modelling crop mixtures enables designing ways to use plant diversity to provide ecosystem services, as long as they include crop management as input. A single modelling approach is not sufficient, however, and complementarities between models may be critical to consider the multiple processes and system components involved at different and relevant spatial and temporal scales. In this article, we present different modelling solutions implemented in a variety of examples to upscale models from local interactions to ecosystem services. We highlight that modelling solutions (i.e. coupling, metamodelling, inverse or hybrid modelling) are built according to modelling objectives (e.g. understand the relative contributions of primary ecological processes to crop mixtures, quantify impacts of the environment and agricultural practices, assess the resulting ecosystem services) rather than to the scales of integration. Many outcomes of multispecies agroecosystems remain to be explored, both experimentally and through the heuristic use of modelling. Combining models to address plant diversity and predict ecosystem services at different scales remains rare but is critical to support the spatial and temporal prediction of the many systems that could be designed.