Animal movement research (an emerging discipline known as movement ecology) has experienced groundbreaking progress in recent years as a consequence of technological and methodological advancements. Animal (including human) movements are the outcome of dynamic interactions between the external environment and individual condition. However, many analytical models and statistical inferences are based around equilibrium space-use distributions that effectively average out transient dynamics over time. To date, this heavy reliance on equilibrium approaches has ignored a significant amount of dynamic information that reflects the behavioral mechanisms by which individuals respond to environmental changes – an increasingly important factor in the wake of accelerated human-induced disturbances. To address this issue, we developed an integrated set of transient movement models focused on extracting ecologically significant dynamical details forgotten by previous steady-state models.
Results/Conclusions
Using cases studies from ecology and epidemiology, we showed that 1) seasonality may modify landscape configuration to impact host movements (e.g., large ungulates) and their contact rates with disease vectors (e.g., mosquitos); 2) disease hotspots can shift over time due to conspecific avoidance, allowing infections to persist in areas bordering neighboring carriers; and 3) vaccine deployment during an outbreak can establish stronger and faster herd immunity through timed redirections of medical effort toward specific population regions. Our results thus demonstrate a radical transformation in research shaped by a growing appreciation of movement transients: the capacity to reveal the past and project the future, enabling us to finally capture a dynamical world that has largely been lost in time.