arXiv:2603.01972v3 Announce Type: replace Abstract: Climate, water, food, energy and governance challenges are interdependent, yet the tools used to study and manage them remain divided by discipline and sector. Coupling sectoral models pair by pair cannot keep pace with the cross-sector and institutional interactions that drive global environmental change. In this Perspective we argue that convergence requires a shared system ontology that preserves meaning as knowledge moves from observation to computation and back to decision-making. Building on a meta-cognition map of scientific knowledge generation, we propose six design criteria for convergent system-of-systems approaches and assess four candidate methods against them, identifying model-based systems engineering paired with hetero-functional graph theory as a candidate "convergence spine". We illustrate the paradigm in the Chesapeake Bay Watershed, where a single ontology links nutrient-flow estimation, institutional analysis of restoration governance, team science and graduate education, and we distinguish what has been implemented from what remains future work. We close with implications for how global environmental change research is organized, funded and taught.