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.