Toward a Conceptual Commons for Theory in Community Ecology

Community ecology has developed a rich and increasingly diverse body of theory, but its rapid expansion has outpaced efforts to compare and synthesize competing frameworks. As a result, semantic ambiguity often masks genuine scientific disagreement. Using theories of species interactions as a lens, I organize this landscape along two axes: formalization (how theories are built) and function (why they are used). Within formalization, I contrast the model-driven culture (which imposes structure) with the data-driven culture (which discovers it), highlighting the distinct forms of misspecification that plague each. Within function, I distinguish three goals: building predictive heuristics, developing definitional frameworks, and running experiments in model worlds. I use this mapping to identify where and why distinct traditions talk past one another, drawing on examples from modern coexistence theory, diversity–stability relationships, niche theory, and network ecology. This analysis provides a diagnostic roadmap for pinpointing why models disagree, justifying the choice of formalization, and aligning questions with appropriate theoretical tools. Beyond diagnosis, I survey current integration efforts and outline practical steps toward synthesis. Finally, I address the human dimension of theoretical practice, arguing that artificial intelligence offers a major opportunity to democratize access to theory if training pivots from derivation to verification. This review lays the groundwork for a conceptual commons where diverse theories can be rigorously compared and productively combined.