Editorial: Advances in modelling and analysis of animal movement

摘要

Understanding why, how, where, and when animals move is fundamental to ecology and evolution (Nathan et al. 2008). Animal movement occurs across a range of spatial and temporal scales, from local foraging and home-range use to seasonal migrations spanning continents. Analyses of movement patterns provide insights at all these scales, with direct applications in conservation, invasive species control, and ecological monitoring. In recent years, technological advances such as high-resolution GPS tracking and biologging have produced an explosion of movement data, allowing more refined recordings of animal movement paths (Williams et al. 2020). However, making sense of this deluge remains challenging, as many movement mechanisms and their ecological consequences such as navigation, foraging strategies, dispersal, and space use are still not fully understood. Integrating rich empirical observations with robust theoretical frameworks is therefore essential to advance movement ecology. This collection of studies offers fresh insights and methodological developments that enhance our understanding of animal movement across spatio-temporal scales and taxa. The contributions span theoretical and empirical methods, individual and population-level analyses, and terrestrial, aquatic, and aerial systems. Here, we synthesise these studies' findings, highlight emerging themes and discuss knowledge gaps and future directions for the field.Quantifying encounters through reaction-diffusion theory Das et al. (2023) revisit a core question: how should we quantify encounters between moving animals? They highlight that different modelling assumptions can lead to vastly different encounter-rate predictions. Using reaction-diffusion theory from statistical physics, they derive analytical expressions for first-encounter probabilities between animals moving within home ranges. They show that treating encounters as firstpassage events yields well-behaved (normalised) probabilities, whereas an approach based on joint occupancy (distance-threshold overlaps) produces non-normalised measures. By mathematically linking these approaches, the researchers explain why the classic "ideal gas" model of encounters (which assumes straight-line random motion and a simple law-of-mass-action) often fails for more realistic diffusive movement. This work provides a rigorous approach for quantifying encounter and interaction rates, relevant to processes like predation, infectious disease transmission, and social contacts among animals.At a broader scale, Getz (2023) offers a hierarchical perspective on movement patterns over an animal's lifetime. In this perspective piece, Getz proposes a movement track segmentation framework that partitions an individual's trajectory into a nested hierarchy of behavioural modes and phases. Anchored by repeatable diel activity routines (e.g. day-night cycles), the framework defines fundamental movement elements and canonical activity modes (such as localised foraging bouts, commuting trips, and resting periods) that can be identified from tracking data. By linking these fine-scale segments to larger-scale phases (e.g. seasonal migrations or lifetime dispersal events), the approach aims to improve forecasts of how animals will adapt their space use under environmental change. A key challenge in global change biology is predicting how shifts in climate or landscape will alter animal ranges and movement patterns (Gomez et al. 2025). This hierarchical approach suggests that understanding scaling-up rules, i.e. how changes in short-term movement behaviour aggregate into longer-term range shifts, could enable more mechanistic predictions of species' responses to changing environments. This framework underscores the importance of multi-scale analysis, connecting individual behavioural decisions to population-level outcomes.In a different ecological context, He et al. (2023) investigate how a diminutive ungulate coexists alongside much larger herb