Agent-based models (ABMs) are increasingly utilized in ecology and related fields, yet concerns persist regarding the lack of consideration for lessons learned from previous models. This study explores the potential of systematically conducted ABM reviews to contribute to cumulative science and theory development by synthesizing individual ABM findings more effectively. We are conducting a meta-review of ABM reviews to assess current practices, compare them to systematic literature review (SLR) literature recommendations, and evaluate their engagement with theory and theory development. Our analysis of the ecology and social science sample reveals that many reviews are not conducted systematically and lack transparency. The analysis step of SLRs holds significant potential to advance theory development. Reviews primarily focus on model design, while other avenues of theory development receive less attention. Our findings suggest ways to improve current practices and may guide future ABM reviews via benchmarks for methodological decisions and dimensions for advancing theory development.

Despite the increasing use of standards for documenting and testing agent-based models (ABMs) and sharing of open access code, most ABMs are still developed from scratch. This is not only inefficient, but also leads to ad hoc and often inconsistent implementations of the same theories in computational code and delays progress in the exploration of the functioning of complex social-ecological systems (SES). We argue that reusable building blocks (RBBs) known from professional software development can mitigate these issues. An RBB is a submodel that represents a particular mechanism or process that is relevant across many ABMs in an application domain, such as plant competition in vegetation models, or reinforcement learning in a behavioural model. RBBs need to be distinguished from modules, which represent entire subsystems and include more than one mechanism and process. While linking modules faces the same challenges as integrating different models in general, RBBs are “atomic” enough to be more easily re-used in different contexts. We describe and provide examples from different domains for how and why building blocks are used in software development, and the benefits of doing so for the ABM community and to individual modellers. We propose a template to guide the development and publication of RBBs and provide example RBBs that use this template. Most importantly, we propose and initiate a strategy for community-based development, sharing and use of RBBs. Individual modellers can have a much greater impact in their field with an RBB than with a single paper, while the community will benefit from increased coherence, facilitating the development of theory for both the behaviour of agents and the systems they form. We invite peers to upload and share their RBBs via our website - preferably referenced by a DOI (digital object identifier obtained e.g. via Zenodo). After a critical mass of candidate RBBs has accumulated, feedback and discussion can take place and both the template and the scope of the envisioned platform can be improved.