High resolution data reveal fundamental steps and turns in animal movements: Animal heading datasets

Animal movement paths display substantial complexity and variability, promoting efforts to identify universal rules and models that best describe them. Using high-resolution (≥ 10 Hz) movement from 43 vertebrate species spanning diverse taxa, body sizes, and lifestyles, we show that paths are universally composed of straight-line steps interspersed with sharp turns, echoing patterns documented in lower taxa such as bacteria. We report how vertebrate “fundamental steps” - straight travel segments between successive detected turns (with Fstepduration as the turn-to-turn interval and Fsteplength as the corresponding distance when displacement is available) - and “fundamental turn angles” (Fturnangles; net changes in travel heading between successive steps) vary with species’ mass, locomotor mode, behaviour, and environment. Here, “fundamental” denotes the finest-scale step/turn events resolvable under our sampling rate and turn-detection criteria; these event-scale steps/turns are intrinsically different from the straight-line segments inferred from low-resolution position data. To explain these relationships, we posit that animals inherently move in a straight line until sensory information signals a better heading, triggering a turn. Across all species examined, animals spent the vast majority of their travel time moving in straight lines (species-level means >90%), with turns representing discrete decision points influenced by body size, locomotor mode, and ecological context. Larger animals turned less frequently, consistent with biomechanical constraints of mass and rotational inertia, while aerial species often exhibited higher turning rates driven by soaring flight demands. We further show that turns can be linked to diverse behavioural drivers, including prey pursuit, obstacle avoidance, predator evasion and exploitation of environmental energy. By explicitly quantifying turns, we clarify how distributions of step durations and turn angles interact to shape movement patterns and why different statistical models (e.g., correlated random walks, Lévy flights) emerge when lower-resolution data are analysed. Finally, we demonstrate how fundamental steps and turns can be incorporated into an agent-based modelling framework using penguins as a case study, enabling reconstruction of realistic tracks and prediction of movement responses to environmental change. Straight-line travel punctuated by decision-driven turns thus emerges as a fundamental principle of vertebrate movement, linking fine-scale movement structure, ecological context, and emergent patterns of space use.