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.