SIMPLACE—a versatile modelling and simulation framework for sustainable crops and agroecosystems

Autoren: Andreas Enders, Murilo Vianna, Thomas Gaiser, Gunther Krauss, Heidi Webber, Amit Kumar Srivastava, Sabine Julia Seidel, Andreas Tewes, Ehsan Eyshi Rezaei, Frank Ewert

DAKIS | 01.2023 | DOI:
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Agricultural system analysis has considerably evolved over the last years, allowing scientists to quantify complex interactions in crops and agroecosystems. Computer-based models have become a central tool for such analysis, using formulated mathematical representations (algorithms) of different biophysical processes to simulate complex system’s behaviour. Nevertheless, the current large variety of algorithms in combination with nonstandardization in their use limits rapid and rigorous model improvement and testing. This is particularly important because contextualization is a key aspect used to formulate the appropriate model structure for a specific research question, framing a clear demand for ‘next generation’ models being modular and flexible. This paper aims to describe the Scientific Impact assessment and Modelling PLatform for Advanced Crop and Ecosystem management (SIMPLACE), which has been developed over the last decade to address the various aforementioned issues and support appropriate model formulations and interoperability. We describe its main technical implementation and features to develop customized model solutions that can be applied to a number of cropping systems with high flexibility, performance and transparency. A brief review of exemplary applications of SIMPLACE is provided covering the different topics, crops and cropping systems, spatial scales and geographies. We stress that standardized documentation of modules, variables ontology and data archives are key requirements to maintain and assist model development and reproducibility. The increasing demand for more complex, diversified and integrated production systems (e.g. intercropping, livestock-grazing, agroforestry) and the associated impacts on sustainable food systems also require the strong collaboration of a multidisciplinary community of modellers and stakeholders.

Publikationsdatum: 01.2023

Verlag: Oxford University Press (OUP)

Quelle: in silico Plants | 1 | | 5

Publikationstyp: Journal-Artikel