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Methodological Insights into Implementing cellular automata models for simulating seagrass dynamics: Responses to global change effects

Abstract

This study introduces an innovative methodology employing Cellular Automata (CA) models to simulate seagrass dynamics in response to global environmental changes. The primary objective is to outline a procedural framework for constructing and deploying CA models applied to seagrass ecosystems, and potentially to other marine or terrestrial environments. The methodology encompasses various components, including conceptualization, workflow delineation, model parameterization, and execution steps. By utilizing Mediterranean and Zanzibari (East Africa) seagrass ecosystems as case studies, we demonstrate the versatility and applicability of the proposed approach across diverse geographical regions, species composition and model components. Through these case studies, we demonstrated how CA models can effectively capture the dynamics of seagrass communities subjected to climate change, invasive species, and nutrient regimes. Despite its strengths, the proposed CA model has limitations, including parameterization complexity and uncertainties related to species-specific environmental thresholds, growth rates and species interactions, alongside the difficulty of validating our models with real-world scenarios. Addressing these limitations in future studies will enhance the model's accuracy and applicability. This study serves as a foundation for future research in other regions and ecosystems, facilitating a better understanding of the complex interactions driving ecosystem dynamics.

Cite this activity

Beca-Carretero P., Meister M., Teichberg M., Moreira-Saporiti A., Schneekloth F. and Reuter H. (2024) Methodological Insights into Implementing cellular automata models for simulating seagrass dynamics: Responses to global change effects. MethodsX 13: 102936. 10.1016/j.mex.2024.102936

Details

Research topics
Date 28.08.2024
Journal MethodsX
Volume 13
Pages 102936
Open Access Open Access (open)
Open Access Status Open Access (open)
Eprints_link https://cris.leibniz-zmt.de/id/eprint/5534
Peer-Reviewed

Research Spectrum

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