Quantifying the movement, behavior, and environmental context of group-living animals using drones and computer vision

Abstract

1. Methods for collecting animal behavior data in natural environments, such as direct observation and bio-logging, are typically limited in spatiotemporal resolution, the number of animals that can be observed, and information about animals' social and physical environments. 2. Video imagery can capture rich information about animals and their environments, but image-based approaches are often impractical due to the challenges of processing large and complex multi-image datasets and transforming resulting data, such as animals' locations, into geographic coordinates. 3. We demonstrate a new system for studying behavior in the wild that uses drone-recorded videos and computer vision approaches to automatically track the location and body posture of free-roaming animals in georeferenced coordinates with high spatiotemporal resolution embedded in contemporaneous 3D landscape models of the surrounding area. 4. We provide two worked examples in which we apply this approach to videos of gelada monkeys and multiple species of group-living African ungulates. We demonstrate how to track multiple animals simultaneously, classify individuals by species and age-sex class, estimate individuals' body postures (poses), and extract environmental features, including topography of the landscape and game trails. 5. By quantifying animal movement and posture, while simultaneously reconstructing a detailed 3D model of the landscape, our approach opens the door to studying the sensory ecology and decision-making of animals within their natural physical and social environments.

ViewShedR: a new open-source tool for cumulative, subtractive and elevated line-of-sight analysis

“…obtained by drones mapping or Lidar; e.g. [37]). With this envisioned feature, a user would be able to add a map that indicates, for example, forested areas, and set a lower distance-to-receiver threshold for targets in the forest, reflecting the expected attenuation of radio signals.…”

Quantifying the movement, behaviour and environmental context of group‐living animals using drones and computer vision

“…Code for the worked examples is available on GitHub at https://github. com/benko ger/overh ead-video -worke d-examples and on Zenodo at https://doi.org/10.5281/zenodo.7622940 (Koger et al, 2023a). All data for the worked examples are archived on EDMOND at https:// doi.org/10.17617/ 3.EMRZGH (Koger et al, 2023b).…”

Mechanisms of group‐hunting in vertebrates

“…To test this hypothesis, however, more fine-scale measurements of the behaviour of multiple predators (simultaneously) are required. Methods include: biologgers or mounted video to record changes in animal behaviour indicative of predator selection or prey detection Christie et al, 2016;Harvey et al, 2016;Hodgson & Koh, 2016;Hubel et al, 2016b,a;Marras et al, 2015b;Jackson et al, 2016;Handley et al, 2018;Torney et al, 2018;Westley et al, 2018;Wilson et al, 2018;Hughey et al, 2018;King et al, 2018;Couzin & Heins, 2022;Hansen et al, 2022;Koger et al, 2023). Differences in predator locomotion and within-group position may indeed correspond to changes in informational state (Bode et al, 2010;Shubkina et al, 2010Shubkina et al, , 2012Herbert-Read et al, 2019) and network-based diffusion analysis (Franz & Nunn, 2009;Hoppitt, 2017) or methodology borrowed from information theory and tested in laboratory animals (Ward et al, 2018;Hansen et al, 2021;Burns et al, 2022) can then assess if these state changes are transferred socially (Fig.…”

“…Our review is inspired by some ideas and methods from the collective behaviour literature as it provides a conceptual framework to understand how interactions between predators can produce group-level patterns (Sumpter, 2006). Accordingly, technology that can track the positions of multiple interacting predators in the wild is of key importance (Kays et al, 2015;Westley et al, 2018;King et al, 2018;Couzin & Heins, 2022;Koger et al, 2023) and can provide especially insightful results when integrated with performance data such as capture rates (Benoit-Bird & Au, 2009;Shubkina, Severtsov & Chepeleva, 2010, 2012Handegard et al, 2012;Hubel et al, 2016a,b). We focus on vertebrate predators as the mechanisms involved in group-hunting eusocial insects, for example, are very different and primarily attributed to complex chemical signalling (Sumpter, 2010), where pheromones provide long-term 'collective memory' to the group.…”