PlantModules.jl: A framework for modular plant modelling

Abstract Plant models are essential for understanding the mechanisms underlying complex plant processes and for predicting growth under varying environmental conditions. They play a central role in plant science and have direct applications in plant breeding, crop management, and related fields. Functional-structural plant models form a widely used class of models that explicitly represent plant structure. Because functional-structural plant models are difficult to implement from scratch, several frameworks have been developed to make them more accessible. However, none of the existing frameworks adopts an acausal modelling approach. Acausal modelling allows users to define systems as differential equation systems without prescribing causal relationships in advance, thereby improving model composability, reusability, and user-friendliness. We introduce PlantModules.jl, an acausal, differential-equation-based functional plant modelling framework designed to integrate with existing structural modelling frameworks for the creation of functional-structural plant models. The framework emphasizes modular model construction, extensibility and customizability, and provides core functionality centred on plant-water relations, offering a broadly applicable foundation for describing plant growth. We illustrate the framework's capabilities through three case studies, including validation against pine tree growth data. As an open-source Julia library, PlantModules.jl provides a flexible platform for future plant modelling efforts.