pyMANGA: Harnessing the Power of Modularity and Reusability for Robust Ecological Modeling
Publikation: Beitrag zu Konferenzen › Wissenschaftliche Vortragsfolien › Beigetragen › Begutachtung
Beitragende
Abstract
Agent-based ecological models are essential tools for understanding and managing ecological systems, especially in the context of rapid global change. However, challenges in validating, reproducing, and comparing these models persist, hindering their effective integration into decision-making processes. In this poster, we present pyMANGA, a free and open-source platform designed to address these challenges. pyMANGA's modular design facilitates the incorporation of different plant growth, resource, and competition concepts, allowing systematic testing of related hypotheses, e.g. to identify dominant processes in forest development. We also present a systematic benchmarking strategy to ensure platform reliability and discuss how pyMANGA can be used to compare models of different levels of abstraction and complexity.
Details
(Fach-)Tagung
Titel | 53rd Annual Conference German Ecological Society |
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Untertitel | The future of sustainable land use across ecosystems, landscapes and biomes |
Kurztitel | GfÖ 2024 |
Veranstaltungsnummer | 2024 |
Dauer | 9 - 13 September 2024 |
Webseite | |
Ort | TUM School of Life Sciences |
Stadt | Freising |
Land | Deutschland |