Historic reference behavior and archetypes of system structure are key tools for creating rigorous system dynamics (SD) models. Modelers often delineate causal relationships by employing common archetypes of dynamic system structure, which produce behaviors such as growth and decline, oscillation, and complex combinations thereof. We extend archetypes to spatial-dynamic models, focusing on structural archetypes that exhibit changing spatial patterns in two-dimensional landscapes. Although many fields employ spatial modeling techniques, analogy-based, causally focused system archetypes remain confined to non-spatial SD models. We draw on spatial analysis literature to explore the influence of space on dynamic relationships and archetypes, including methods for articulating ÒspaceÓ and expressing feedback. We offer simple examples of spatial system archetypes and explore network structures for spatially extending SD models. By doing this, we argue for spatial modeling techniques that parallel the learn-by-analogy environment that archetypes have promoted in aspatial SD research.