Climate–ecosystem modelling made easy: The Land Sites Platform

• DOI: 10.1111/gcb.16808
• Publication Date: 2023-06-12T03:15:07Z
• Authors: Lasse T. Keetz; Eva Lieungh; Kaveh Karimi‐Asli; Sonya R. Geange; Emiliano Gelati; Hui Tang; Yeliz A. Yilmaz; Kjetil S. Aas; Inge H. J. Althuizen; Anders Bryn; Stefanie Falk; Rosie Fisher; Anne Fouilloux; Peter Horvath; Sunniva Indrehus; Hanna Lee; Danica Lombardozzi; Frans‐Jan W. Parm...; Norbert Pirk; Vigdis Vandvik; Ane V. Vollsnes; Olav Skarpaas; Frode Stordal; Lena M. Tallaksen
• Keywords: Interface (matter)

Abstract Dynamic Global Vegetation Models (DGVMs) provide a state‐of‐the‐art process‐based approach to study the complex interplay between vegetation and its physical environment. For example, they help predict how terrestrial plants interact with climate, soils, disturbance competition for resources. We argue that there is untapped potential use of DGVMs in ecological ecophysiological research. One fundamental barrier realize this many researchers relevant expertize (ecology, plant physiology, soil science, etc.) lack access technical resources or awareness research DGVMs. Here we present Land Sites Platform (LSP): new software facilitates single‐site simulations Functionally Assembled Terrestrial Ecosystem Simulator, an advanced DGVM coupled Community Model. The LSP includes Graphical User Interface Application Programming Interface, which improve user experience lower thresholds installing these model architectures setting up experiments. distributed via version‐controlled containers; students can run directly on their personal computers servers, relatively low hardware requirements, different operating systems. Version 1.0 supports site‐level simulations. input data 20 established geo‐ecological observation sites Norway workflows add generic from public global datasets. makes standard experiments default easily achievable (e.g., educational introductory purposes) while retaining flexibility more scientific uses. further tools visualize output, including simple examples relate predictions local observations. improves land surface modelling as building block community cyberinfrastructure may inspire avenues mechanistic ecosystem across disciplines.