Why, how, where, and when animals move remain fundamental questions in movement ecology. Understanding movement patterns provides insights across spatial and temporal scales, from fine-scale foraging and home range exploration to long-distance dispersal and migration. These insights have direct implications for conservation, biodiversity management, biological invasions, and ecological monitoring.

Since the first volume of this Research Topic published on the 7th of August 2025, technological and analytical advances have continued to reshape the field. High-resolution biologging, remote sensing, and the integration of artificial intelligence with statistical and mechanistic models now allow researchers to explore animal movements in unprecedented detail. These developments create opportunities to address outstanding challenges such as predicting animal responses to global environmental change, linking movement with ecological interactions, and comparing strategies across diverse taxa and ecosystems.

This second volume aims to bring together theoretical and empirical contributions that advance our understanding of animal movement. We welcome original research, perspectives, and reviews spanning terrestrial, aquatic, and volant organisms, at any organizational level including individuals, populations, or communities. Submissions may focus on methodological innovations, conceptual frameworks, or applied case studies, using approaches ranging from mathematical and statistical modelling to data-driven machine learning.

By compiling cutting-edge work at the intersection of modelling, data analysis, and ecology, this Research Topic will continue to push forward the boundaries of how movement is studied, interpreted, and applied.

To further our understanding, we invite contributions addressing, but not limited to, the following themes:

1. Novel mathematical and mechanistic modelling approaches to animal movement.
Development of theoretical and mathematical frameworks for describing and predicting movement processes across spatial and temporal scales.

2. Integrative statistical, computational, and machine learning models for movement analysis.
Advances that merge data-driven and process-based methods, to uncover behavioral modes, environmental drivers, and emergent dynamics in movement data.

3. Movement responses and predictive models under global environmental change.
Studies modelling how habitat alteration, climate variability, and anthropogenic pressures influence movement behavior, dispersal, and migration.

4. Linking movement to ecological interactions and ecosystem processes.
Frameworks connecting movement with population dynamics, trophic interactions, disease spread, seed dispersal, or ecosystem functioning, integrating movement with ecological networks and community dynamics.

5. Comparative and cross-taxonomic analyses of movement strategies.
Quantitative comparisons of movement behaviors, scaling laws, and strategy diversity across species, guilds, habitats, and functional groups, aimed at identifying general principles and trait-based patterns.

6. Methodological challenges and applied pathways in movement data and management.
Addressing data quality, sampling bias, model evaluation, reproducibility, and computational tools; translating methodological advances into conservation, wildlife management, and policy applications.

Are you interested in contributing a manuscript to this Research Topic?

Advances in Modelling and Analysis of Animal Movement- Volume II