Mobile animal groups provide some of the most compelling examples of self-organization in the natural world. While field observations of songbird flocks wheeling in the sky or anchovy schools fleeing from predators have inspired considerable interest in the mechanics of collective motion, the challenge of simultaneously monitoring multiple animals in the field has historically limited our capacity to study collective behaviour of wild animal groups with precision. However, recent technological advancements now present exciting opportunities to overcome many of these limitations. Here we review existing methods used to collect data on the movements and interactions of multiple animals in a natural setting. We then survey emerging technologies that are poised to revolutionize the study of collective animal behaviour by extending the spatial and temporal scales of inquiry, increasing data volume and quality, and expediting the post-processing of raw data.This article is part of the theme issue 'Collective movement ecology'.

Recent increases in human disturbance pose significant threats to migratory species using collective movement strategies. Key threats to migrants may differ depending on behavioural traits (e.g. collective navigation), taxonomy and the environmental system (i.e. freshwater, marine or terrestrial) associated with migration. We quantitatively assess how collective navigation, taxonomic membership and environmental system impact species' vulnerability by (i) evaluating population change in migratory and non-migratory bird, mammal and fish species using the Living Planet Database (LPD), (ii) analysing the role of collective navigation and environmental system on migrant extinction risk using International Union for Conservation of Nature (IUCN) classifications and (iii) compiling literature on geographical range change of migratory species. Likelihood of population decrease differed by taxonomic group: migratory birds were more likely to experience annual declines than non-migrants, while mammals displayed the opposite pattern. Within migratory species in IUCN, we observed that collective navigation and environmental system were important predictors of extinction risk for fishes and birds, but not for mammals, which had overall higher extinction risk than other taxa. We found high phylogenetic relatedness among collectively navigating species, which could have obscured its importance in determining extinction risk. Overall, outputs from these analyses can help guide strategic interventions to conserve the most vulnerable migrations.This article is part of the theme issue 'Collective movement ecology'.

The ecological importance of the common hippopotamus (Hippopotamus amphibius) in aquatic ecosystems is becoming increasingly well known. These unique megaherbivores are also likely to have a formative influence on the terrestrial ecosystems in which they forage. In this study, we employed a novel exclosure design to exclude H. amphibius from experimental plots on near-river grasslands. Our three-year implementation of this experiment revealed a substantial influence of H. amphibius removal on both plant communities and soil chemistry. H. amphibius significantly reduced grassland canopy height, increased the leafiness of common grasses, reduced woody plant abundance and size, and increased the concentrations of several soil elements. Many of the soil chemistry changes that we experimentally induced by exclusion of H. amphibius were mirrored in the soil chemistry differences between naturally occurring habitats of frequent (grazing lawns) and infrequent (shrub forest) use by H. amphibius and other grazing herbivores. In contrast to existing hypotheses regarding grazing species, we found that H. amphibius had little effect on local plant species richness. Simultaneous observations of exclosures designed to remove all large herbivores revealed that H. amphibius removal had ecologically significant impacts, but that the removal of all species of large herbivores generated more pronounced impacts than the removal of H. amphibius alone. In aggregate, our results suggest that H. amphibius have myriad effects on their terrestrial habitats that likely improve the quality of forage available for other herbivores. We suggest that ongoing losses of this vulnerable megaherbivore are likely to cause significant ecological change.

The ability to move is essential for animals to find mates, escape predation, and meet energy and water demands. This is especially important across grazing systems where vegetation productivity can vary drastically between seasons or years. With grasslands undergoing significant changes due to climate change and anthropogenic development, there is an urgent need to determine the relative impacts of these pressures on the movement capacity of native herbivores. To measure these impacts, we fitted 36 white-bearded wildebeest (Connochaetes taurinus) with GPS collars across three study areas in southern Kenya (Amboseli Basin, Athi-Kaputiei Plains, and Mara) to test the relationship between movement (e.g., directional persistence, speed, home range crossing time) and gradients of vegetation productivity (i.e., NDVI) and anthropogenic disturbance. As expected, wildebeest moved the most (21.0 km day–1; CI: 18.7–23.3) across areas where movement was facilitated by low human footprint and necessitated by low vegetation productivity (Amboseli Basin). However, in areas with moderate vegetation productivity (Athi-Kaputiei Plains), wildebeest moved the least (13.3 km day–1; CI: 11.0–15.5). This deviation from expectations was largely explained by impediments to movement associated with a large human footprint. Notably, the movements of wildebeest in this area were also less directed than the other study populations, suggesting that anthropogenic disturbance (i.e., roads, fences, and the expansion of settlements) impacts the ability of wildebeest to move and access available resources. In areas with high vegetation productivity and moderate human footprint (Mara), we observed intermediate levels of daily movement (14.2 km day–1; CI: 12.3–16.1). Wildebeest across each of the study systems used grassland habitats outside of protected areas extensively, highlighting the importance of unprotected landscapes for conserving mobile species. These results provide unique insights into the interactive effects of climate and anthropogenic development on the movements of a dominant herbivore in East Africa and present a cautionary tale for the development of grazing ecosystems elsewhere.

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Reintroduced animals—especially those raised in captivity—are faced with the unique challenge of navigating a wholly unfamiliar environment, and often make erratic or extensive movements after release. Naïveté to the reintroduction landscape can be costly, e.g., through increased energy expenditure, greater exposure to predation, and reduced opportunities to forage. Integration with an extant population may provide opportunities for social information transfer. However, in the absence of interactions with residents, it is unclear how individual and social learning may affect an animal’s ability to track resources in an unfamiliar landscape. We use integrated step selection functions (iSSFs) to address these knowledge gaps, by evaluating the extent to which environmental factors, individual experience (time since release), and social information-sharing (group size) influence movement decisions by scimitar-horned oryx (Oryx dammah) reintroduced into their native range for the first time in ca. 30 years. We found that both experience and social factors influenced the habitat selection and movement behavior of reintroduced oryx. Of four candidate iSSFs, the model that included environmental, experience, and group size variables performed best in both dry and wet periods. Statistically significant interaction terms between environmental variables and experience were generally larger than similar terms for group size, indicating that experience may affect habitat selection by reintroduced oryx more strongly than social factors. These findings may inform the management of recovering wildlife populations, update widely-held expectations about how released ungulates acclimate to novel landscapes, and demonstrate the utility of long-term monitoring of reintroduced populations.

Climatic variability, resource availability, and anthropogenic impacts heavily influence an animal's home range. This makes home range size an effective metric for understanding how variation in environmental factors alter the behavior and spatial distribution of animals. In this study, we estimated home range size of African elephants (Loxodonta africana) across four sites in Namibia, along a gradient of precipitation and human impact, and investigated how these gradients influence the home range size on regional and site scales. Additionally, we estimated the time individuals spent within protected area boundaries. The mean 50% autocorrelated kernel density estimate for home range was 2200 km2 [95% CI:1500–3100 km2]. Regionally, precipitation and vegetation were the strongest predictors of home range size, accounting for a combined 53% of observed variation. However, different environmental covariates explained home range variation at each site. Precipitation predicted most variation (up to 74%) in home range sizes (n = 66) in the drier western sites, while human impacts explained 71% of the variation in home range sizes (n = 10) in Namibia's portion of the Kavango‐Zambezi Transfrontier Conservation Area. Elephants in all study areas maintained high fidelity to protected areas, spending an average of 85% of time tracked on protected lands. These results suggest that while most elephant space use in Namibia is driven by natural dynamics, some elephants are experiencing changes in space use due to human modification.

New satellite remote sensing and machine learning techniques offer untapped possibilities to monitor global biodiversity with unprecedented speed and precision. These efficiencies promise to reveal novel ecological insights at spatial scales which are germane to the management of populations and entire ecosystems. Here, we present a robust transferable deep learning pipeline to automatically locate and count large herds of migratory ungulates (wildebeest and zebra) in the Serengeti-Mara ecosystem using fine-resolution (38-50 cm) satellite imagery. The results achieve accurate detection of nearly 500,000 individuals across thousands of square kilometers and multiple habitat types, with an overall F1-score of 84.75% (Precision: 87.85%, Recall: 81.86%). This research demonstrates the capability of satellite remote sensing and machine learning techniques to automatically and accurately count very large populations of terrestrial mammals across a highly heterogeneous landscape. We also discuss the potential for satellite-derived species detections to advance basic understanding of animal behavior and ecology.