Aggregations are common in biological systems at a range of scales and may be driven by exogenous constraints such as environmental heterogeneity and resource availability or by “self-organizing” interactions among individuals. One mechanism leading to self-organized animal aggregations is captured by Hamilton’s “selfish herd” hypothesis, which suggests that aggregations may be driven by an individual’s effort to minimize their risk of predation by surrounding themselves with conspecifics. In this talk, I will describe my lab’s research into the spatial dynamics of nesting Adélie penguins (Pygoscelis adeliae), whose nest site fidelity frustrates a fluid re-arrangement of the nesting colony through time. Using drones, satellites, and agent-based modelling, I show how the spatial conformations of penguin colonies are driven by a convolution of landscape terrain, stochastic fluctuations in abundance, and predation-driven behavior. This spatial patterning, which has direct analogs in other domains of statistical mechanics and condensed matter physics, is informative of past population dynamics and represents an early warning sign of population collapse of practical value for conservation and management. Finally, I will discuss mathematical approaches to describing colony shape and shape complexity, and the interplay between shape descriptors and our long-standing efforts to use computer vision to automate the interpretation of satellite imagery for monitoring penguin colonies.