1
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Kuntz G, Huang J, Rask M, Lindgren-Ruby A, Shinsato JY, Bi D, Tabatabai AP. Spatial confinement affects the heterogeneity and interactions between shoaling fish. Sci Rep 2024; 14:12296. [PMID: 38811673 DOI: 10.1038/s41598-024-63245-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2024] [Accepted: 05/27/2024] [Indexed: 05/31/2024] Open
Abstract
Living objects are able to consume chemical energy and process information independently from others. However, living objects can coordinate to form ordered groups such as schools of fish. This work considers these complex groups as living materials and presents imaging-based experiments of laboratory schools of fish to understand how activity, which is a non-equilibrium feature, affects the structure and dynamics of a group. We use spatial confinement to control the motion and structure of fish within quasi-2D shoals of fish and use image analysis techniques to make quantitative observations of the structures, their spatial heterogeneity, and their temporal fluctuations. Furthermore, we utilize Monte Carlo simulations to replicate the experimentally observed data which provides insight into the effective interactions between fish and confirms the presence of a confinement-based behavioral preference transition. In addition, unlike in short-range interacting systems, here structural heterogeneity and dynamic activities are positively correlated as a result of complex interplay between spatial arrangement and behavioral dynamics in fish collectives.
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Affiliation(s)
- Gabriel Kuntz
- Department of Physics, Seattle University, Seattle, WA, 98122, USA
| | - Junxiang Huang
- Department of Physics, Northeastern University, Boston, MA, 02115, USA
| | - Mitchell Rask
- Department of Physics, Seattle University, Seattle, WA, 98122, USA
| | | | - Jacob Y Shinsato
- Department of Physics, Seattle University, Seattle, WA, 98122, USA
| | - Dapeng Bi
- Department of Physics, Northeastern University, Boston, MA, 02115, USA
| | - A Pasha Tabatabai
- Department of Physics, Seattle University, Seattle, WA, 98122, USA.
- Physics Department, California Polytechnic State University, San Luis Obispo, CA, 93410, USA.
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2
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Kryuchkov NP, Nasyrov AD, Gursky KD, Yurchenko SO. Influence of anomalous agents on the dynamics of an active system. Phys Rev E 2024; 109:034601. [PMID: 38632726 DOI: 10.1103/physreve.109.034601] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2023] [Accepted: 01/25/2024] [Indexed: 04/19/2024]
Abstract
Swarming behavior in systems of self-propelled particles, whether biological or artificial, has received increased attention in recent years. Here, we show that even a small number of particles with anomalous behavior can change dramatically collective dynamics of the swarming system and can impose unusual behavior and transitions between dynamic states. Our results pave the way to practical approaches and concepts of multiagent dynamics in groups of flocking animals: birds, insects, and fish, i.e., active and living soft matter.
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Affiliation(s)
- Nikita P Kryuchkov
- Bauman Moscow State Technical University, 2nd Baumanskaya Street 5, 105005 Moscow, Russia
| | - Artur D Nasyrov
- Bauman Moscow State Technical University, 2nd Baumanskaya Street 5, 105005 Moscow, Russia
| | - Konstantin D Gursky
- Bauman Moscow State Technical University, 2nd Baumanskaya Street 5, 105005 Moscow, Russia
| | - Stanislav O Yurchenko
- Bauman Moscow State Technical University, 2nd Baumanskaya Street 5, 105005 Moscow, Russia
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3
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Yan X, Wang X, Zhao Y, Zhu Q, Yang L, Li Z. Collective decision-making and spatial patterns in orientation of an endemic ungulate on the Tibetan Plateau. Curr Zool 2024; 70:45-58. [PMID: 38476135 PMCID: PMC10926256 DOI: 10.1093/cz/zoad004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2022] [Accepted: 01/31/2023] [Indexed: 03/14/2024] Open
Abstract
Group living animals form striking aggregation patterns and display synchronization, polarization, and collective intelligence. Though many collective behavioral studies have been conducted on small animals like insects and fish, research on large animals is still rare due to the limited availability of field collective data. We used drones to record videos and analyzed the decision-making and behavioral spatial patterns in orientation of Kiang (Tibetan wild ass, Equus kiang). Leadership is unevenly distributed among Kiang, with the minority initiating majority behavior-shift decisions. Decisions of individual to join are driven by imitation between group members, and are largely dependent on the number of members who have already joined. Kiang respond to the behavior and position of neighbors through different strategies. They strongly polarize when moving, therefore adopting a linear alignment. When vigilant, orientation deviation increases as they form a tighter group. They remain scattered while feeding and, in that context, adopt a side-by-side alignment. This study reveals partially-shared decision-making among Kiang, whereby copying neighbors provides the wisdom to thrive in harsh conditions. This study also suggests that animals' spatial patterns in orientation depend largely on their behavioral states in achieving synchronization.
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Affiliation(s)
- Xueting Yan
- Lab of Animal Behavior & Conservation, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210023, China
| | - Xu Wang
- Lab of Animal Behavior & Conservation, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210023, China
| | - Yumeng Zhao
- Lab of Animal Behavior & Conservation, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210023, China
| | - Qin Zhu
- Lab of Animal Behavior & Conservation, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210023, China
| | - Le Yang
- Tibet Plateau Institute of Biology, Lhasa, 850000, China
| | - Zhongqiu Li
- Lab of Animal Behavior & Conservation, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210023, China
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4
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Thompson PR, Harrington PD, Mallory CD, Lele SR, Bayne EM, Derocher AE, Edwards MA, Campbell M, Lewis MA. Simultaneous estimation of the temporal and spatial extent of animal migration using step lengths and turning angles. MOVEMENT ECOLOGY 2024; 12:1. [PMID: 38191509 PMCID: PMC10775566 DOI: 10.1186/s40462-023-00444-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Accepted: 12/19/2023] [Indexed: 01/10/2024]
Abstract
BACKGROUND Animals of many different species, trophic levels, and life history strategies migrate, and the improvement of animal tracking technology allows ecologists to collect increasing amounts of detailed data on these movements. Understanding when animals migrate is important for managing their populations, but is still difficult despite modelling advancements. METHODS We designed a model that parametrically estimates the timing of migration from animal tracking data. Our model identifies the beginning and end of migratory movements as signaled by change-points in step length and turning angle distributions. To this end, we can also use the model to estimate how an animal's movement changes when it begins migrating. In addition to a thorough simulation analysis, we tested our model on three datasets: migratory ferruginous hawks (Buteo regalis) in the Great Plains, barren-ground caribou (Rangifer tarandus groenlandicus) in northern Canada, and non-migratory brown bears (Ursus arctos) from the Canadian Arctic. RESULTS Our simulation analysis suggests that our model is most useful for datasets where an increase in movement speed or directional autocorrelation is clearly detectable. We estimated the beginning and end of migration in caribou and hawks to the nearest day, while confirming a lack of migratory behaviour in the brown bears. In addition to estimating when caribou and ferruginous hawks migrated, our model also identified differences in how they migrated; ferruginous hawks achieved efficient migrations by drastically increasing their movement rates while caribou migration was achieved through significant increases in directional persistence. CONCLUSIONS Our approach is applicable to many animal movement studies and includes parameters that can facilitate comparison between different species or datasets. We hope that rigorous assessment of migration metrics will aid understanding of both how and why animals move.
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Affiliation(s)
- Peter R Thompson
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada.
| | - Peter D Harrington
- Department of Mathematics, University of British Columbia, Vancouver, BC, Canada
- Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada
| | | | - Subhash R Lele
- Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada
| | - Erin M Bayne
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Andrew E Derocher
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
| | - Mark A Edwards
- Office of the Chief Scientist, Environment and Protected Areas, Government of Alberta, Edmonton, AB, Canada
- Department of Renewable Resources, University of Alberta, Edmonton, AB, Canada
| | | | - Mark A Lewis
- Department of Biological Sciences, University of Alberta, Edmonton, AB, Canada
- Department of Mathematical and Statistical Sciences, University of Alberta, Edmonton, AB, Canada
- Department of Biology, University of Victoria, Victoria, BC, Canada
- Department of Mathematics and Statistics, University of Victoria, Victoria, BC, Canada
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5
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Tan P, Miles CE. Intrinsic statistical separation of subpopulations in heterogeneous collective motion via dimensionality reduction. Phys Rev E 2024; 109:014403. [PMID: 38366514 DOI: 10.1103/physreve.109.014403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Accepted: 12/12/2023] [Indexed: 02/18/2024]
Abstract
Collective motion of locally interacting agents is found ubiquitously throughout nature. The inability to probe individuals has driven longstanding interest in the development of methods for inferring the underlying interactions. In the context of heterogeneous collectives, where the population consists of individuals driven by different interactions, existing approaches require some knowledge about the heterogeneities or underlying interactions. Here, we investigate the feasibility of identifying the identities in a heterogeneous collective without such prior knowledge. We numerically explore the behavior of a heterogeneous Vicsek model and find sufficiently long trajectories intrinsically cluster in a principal component analysis-based dimensionally reduced model-agnostic description of the data. We identify how heterogeneities in each parameter in the model (interaction radius, noise, population proportions) dictate this clustering. Finally, we show the generality of this phenomenon by finding similar behavior in a heterogeneous D'Orsogna model. Altogether, our results establish and quantify the intrinsic model-agnostic statistical disentanglement of identities in heterogeneous collectives.
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Affiliation(s)
- Pei Tan
- Mathematical, Computational, and Systems Biology Graduate Program, University of California, Irvine 92697, USA
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6
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Ko H, Lauder G, Nagpal R. The role of hydrodynamics in collective motions of fish schools and bioinspired underwater robots. J R Soc Interface 2023; 20:20230357. [PMID: 37876271 PMCID: PMC10598440 DOI: 10.1098/rsif.2023.0357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 10/02/2023] [Indexed: 10/26/2023] Open
Abstract
Collective behaviour defines the lives of many animal species on the Earth. Underwater swarms span several orders of magnitude in size, from coral larvae and krill to tunas and dolphins. Agent-based algorithms have modelled collective movements of animal groups by use of social forces, which approximate the behaviour of individual animals. But details of how swarming individuals interact with the fluid environment are often under-examined. How do fluid forces shape aquatic swarms? How do fish use their flow-sensing capabilities to coordinate with their schooling mates? We propose viewing underwater collective behaviour from the framework of fluid stigmergy, which considers both physical interactions and information transfer in fluid environments. Understanding the role of hydrodynamics in aquatic collectives requires multi-disciplinary efforts across fluid mechanics, biology and biomimetic robotics. To facilitate future collaborations, we synthesize key studies in these fields.
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Affiliation(s)
- Hungtang Ko
- Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ, USA
| | - George Lauder
- Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | - Radhika Nagpal
- Mechanical and Aerospace Engineering, Princeton University, Princeton, NJ, USA
- Computer Science, Princeton University, Princeton, NJ, USA
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7
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Hansen MJ, Domenici P, Bartashevich P, Burns A, Krause J. Mechanisms of group-hunting in vertebrates. Biol Rev Camb Philos Soc 2023; 98:1687-1711. [PMID: 37199232 DOI: 10.1111/brv.12973] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 04/24/2023] [Accepted: 04/26/2023] [Indexed: 05/19/2023]
Abstract
Group-hunting is ubiquitous across animal taxa and has received considerable attention in the context of its functions. By contrast much less is known about the mechanisms by which grouping predators hunt their prey. This is primarily due to a lack of experimental manipulation alongside logistical difficulties quantifying the behaviour of multiple predators at high spatiotemporal resolution as they search, select, and capture wild prey. However, the use of new remote-sensing technologies and a broadening of the focal taxa beyond apex predators provides researchers with a great opportunity to discern accurately how multiple predators hunt together and not just whether doing so provides hunters with a per capita benefit. We incorporate many ideas from collective behaviour and locomotion throughout this review to make testable predictions for future researchers and pay particular attention to the role that computer simulation can play in a feedback loop with empirical data collection. Our review of the literature showed that the breadth of predator:prey size ratios among the taxa that can be considered to hunt as a group is very large (<100 to >102 ). We therefore synthesised the literature with respect to these predator:prey ratios and found that they promoted different hunting mechanisms. Additionally, these different hunting mechanisms are also related to particular stages of the hunt (search, selection, capture) and thus we structure our review in accordance with these two factors (stage of the hunt and predator:prey size ratio). We identify several novel group-hunting mechanisms which are largely untested, particularly under field conditions, and we also highlight a range of potential study organisms that are amenable to experimental testing of these mechanisms in connection with tracking technology. We believe that a combination of new hypotheses, study systems and methodological approaches should help push the field of group-hunting in new directions.
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Affiliation(s)
- Matthew J Hansen
- Fish Biology, Fisheries and Aquaculture, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm 310, Berlin, 12587, Germany
| | - Paolo Domenici
- IBF-CNR, Consiglio Nazionale delle Ricerche, Area di Ricerca San Cataldo, Via G. Moruzzi No. 1, Pisa, 56124, Italy
- IAS-CNR, Località Sa Mardini, Torregrande, Oristano, 09170, Italy
| | - Palina Bartashevich
- Faculty of Life Science, Humboldt-Universität zu Berlin, Invalidenstrasse 42, Berlin, 10115, Germany
- Cluster of Excellence "Science of Intelligence," Technical University of Berlin, Marchstr. 23, Berlin, 10587, Germany
| | - Alicia Burns
- Faculty of Life Science, Humboldt-Universität zu Berlin, Invalidenstrasse 42, Berlin, 10115, Germany
- Cluster of Excellence "Science of Intelligence," Technical University of Berlin, Marchstr. 23, Berlin, 10587, Germany
| | - Jens Krause
- Fish Biology, Fisheries and Aquaculture, Leibniz Institute of Freshwater Ecology and Inland Fisheries, Müggelseedamm 310, Berlin, 12587, Germany
- Faculty of Life Science, Humboldt-Universität zu Berlin, Invalidenstrasse 42, Berlin, 10115, Germany
- Cluster of Excellence "Science of Intelligence," Technical University of Berlin, Marchstr. 23, Berlin, 10587, Germany
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8
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Ozogány K, Kerekes V, Fülöp A, Barta Z, Nagy M. Fine-scale collective movements reveal present, past and future dynamics of a multilevel society in Przewalski's horses. Nat Commun 2023; 14:5096. [PMID: 37669934 PMCID: PMC10480438 DOI: 10.1038/s41467-023-40523-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 07/31/2023] [Indexed: 09/07/2023] Open
Abstract
Studying animal societies needs detailed observation of many individuals, but technological advances offer new opportunities in this field. Here, we present a state-of-the-art drone observation of a multilevel herd of Przewalski's horses, consisting of harems (one-male, multifemale groups). We track, in high spatio-temporal resolution, the movements of 238 individually identified horses on drone videos, and combine movement analyses with demographic data from two decades of population monitoring. Analysis of collective movements reveals how the structure of the herd's social network is related to kinship and familiarity of individuals. The network centrality of harems is related to their age and how long the harem stallions have kept harems previously. Harems of genetically related stallions are closer to each other in the network, and female exchange is more frequent between closer harems. High movement similarity of females from different harems predicts becoming harem mates in the future. Our results show that only a few minutes of fine-scale movement tracking combined with high throughput data driven analysis can reveal the structure of a society, reconstruct past group dynamics and predict future ones.
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Affiliation(s)
- Katalin Ozogány
- ELKH-DE Behavioural Ecology Research Group, University of Debrecen, Egyetem tér 1, Debrecen, 4032, Hungary.
- Department of Evolutionary Zoology and Human Biology, University of Debrecen, Egyetem tér 1, Debrecen, 4032, Hungary.
| | - Viola Kerekes
- Hortobágy National Park Directorate, Sumen u. 2, Debrecen, 4024, Hungary
| | - Attila Fülöp
- ELKH-DE Behavioural Ecology Research Group, University of Debrecen, Egyetem tér 1, Debrecen, 4032, Hungary
- Department of Evolutionary Zoology and Human Biology, University of Debrecen, Egyetem tér 1, Debrecen, 4032, Hungary
- Evolutionary Ecology Group, Hungarian Department of Biology and Ecology, Babeș-Bolyai University, Str. Clinicilor 5-7, 400006, Cluj-Napoca, Romania
- Centre for Systems Biology, Biodiversity and Bioresources (3B), Babeș-Bolyai University, Str. Clinicilor 5-7, 400006, Cluj-Napoca, Romania
- STAR-UBB Institute of Advanced Studies in Science and Technology, Babeş-Bolyai University, Str. Mihail Kogălniceanu 1, 400084, Cluj-Napoca, Romania
| | - Zoltán Barta
- ELKH-DE Behavioural Ecology Research Group, University of Debrecen, Egyetem tér 1, Debrecen, 4032, Hungary
- Department of Evolutionary Zoology and Human Biology, University of Debrecen, Egyetem tér 1, Debrecen, 4032, Hungary
| | - Máté Nagy
- MTA-ELTE "Lendület" Collective Behaviour Research Group, Hungarian Academy of Sciences, Pázmány P. Stny. 1A, Budapest, 1117, Hungary.
- Department of Biological Physics, Eötvös Loránd University, Pázmány P. Stny. 1A, Budapest, 1117, Hungary.
- MTA-ELTE Statistical and Biological Physics Research Group, Hungarian Academy of Sciences, Pázmány P. Stny. 1A, Budapest, 1117, Hungary.
- Department of Collective Behavior, Max Planck Institute of Animal Behavior, Universitätsstraße 10, 78457, Konstanz, Germany.
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9
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Rathore A, Sharma A, Shah S, Sharma N, Torney C, Guttal V. Multi-Object Tracking in Heterogeneous environments (MOTHe) for animal video recordings. PeerJ 2023; 11:e15573. [PMID: 37397020 PMCID: PMC10309051 DOI: 10.7717/peerj.15573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2022] [Accepted: 05/25/2023] [Indexed: 07/04/2023] Open
Abstract
Aerial imagery and video recordings of animals are used for many areas of research such as animal behaviour, behavioural neuroscience and field biology. Many automated methods are being developed to extract data from such high-resolution videos. Most of the available tools are developed for videos taken under idealised laboratory conditions. Therefore, the task of animal detection and tracking for videos taken in natural settings remains challenging due to heterogeneous environments. Methods that are useful for field conditions are often difficult to implement and thus remain inaccessible to empirical researchers. To address this gap, we present an open-source package called Multi-Object Tracking in Heterogeneous environments (MOTHe), a Python-based application that uses a basic convolutional neural network for object detection. MOTHe offers a graphical interface to automate the various steps related to animal tracking such as training data generation, animal detection in complex backgrounds and visually tracking animals in the videos. Users can also generate training data and train a new model which can be used for object detection tasks for a completely new dataset. MOTHe doesn't require any sophisticated infrastructure and can be run on basic desktop computing units. We demonstrate MOTHe on six video clips in varying background conditions. These videos are from two species in their natural habitat-wasp colonies on their nests (up to 12 individuals per colony) and antelope herds in four different habitats (up to 156 individuals in a herd). Using MOTHe, we are able to detect and track individuals in all these videos. MOTHe is available as an open-source GitHub repository with a detailed user guide and demonstrations at: https://github.com/tee-lab/MOTHe-GUI.
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Affiliation(s)
- Akanksha Rathore
- Centre for Ecological Sciences, Indian Institute of Science, Bangalore, India
| | - Ananth Sharma
- Centre for Ecological Sciences, Indian Institute of Science, Bangalore, India
| | - Shaan Shah
- Department of Electrical Engineering, Indian Institute of Technology, Bombay, Mumbai, India
| | - Nitika Sharma
- Centre for Ecological Sciences, Indian Institute of Science, Bangalore, India
- Department of Ecology and Evolutionary Biology, University of California, Los Angeles, Los Angeles, United States of America
| | - Colin Torney
- School of Mathematics and Statistics, University of Glasgow, Glasgow, United Kingdom
| | - Vishwesha Guttal
- Centre for Ecological Sciences, Indian Institute of Science, Bangalore, India
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10
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Maeda T, Yamamoto S. Drone Observation for the Quantitative Study of Complex Multilevel Societies. Animals (Basel) 2023; 13:1911. [PMID: 37370421 DOI: 10.3390/ani13121911] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/30/2023] [Accepted: 06/06/2023] [Indexed: 06/29/2023] Open
Abstract
Unmanned aerial vehicles (drones) have recently been used in various behavioral ecology studies. However, their application has been limited to single groups, and most studies have not implemented individual identification. A multilevel society refers to a social structure in which small stable "core units" gather and make a larger, multiple-unit group. Here, we introduce recent applications of drone technology and individual identification to complex social structures involving multiple groups, such as multilevel societies. Drones made it possible to obtain the identification, accurate positioning, or movement of more than a hundred individuals in a multilevel social group. In addition, in multilevel social groups, drones facilitate the observation of heterogeneous spatial positioning patterns and mechanisms of behavioral propagation, which are different from those in a single-level group. Such findings may contribute to the quantitative definition and assessment of multilevel societies and enhance our understanding of mechanisms of multiple group aggregation. The application of drones to various species may resolve various questions related to multilevel societies.
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Affiliation(s)
- Tamao Maeda
- Wildlife Research Center, Kyoto University, Kyoto 606-8203, Japan
- Research Center for Integrative Evolutionary Science, The Graduate University of Advanced Science (SOKENDAI), Hayama 240-0193, Japan
| | - Shinya Yamamoto
- Institute of Advanced Study, Kyoto University, Kyoto 606-8501, Japan
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11
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Sridhar VH, Davidson JD, Twomey CR, Sosna MMG, Nagy M, Couzin ID. Inferring social influence in animal groups across multiple timescales. Philos Trans R Soc Lond B Biol Sci 2023; 378:20220062. [PMID: 36802787 PMCID: PMC9939267 DOI: 10.1098/rstb.2022.0062] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2023] Open
Abstract
Many animal behaviours exhibit complex temporal dynamics, suggesting there are multiple timescales at which they should be studied. However, researchers often focus on behaviours that occur over relatively restricted temporal scales, typically ones that are more accessible to human observation. The situation becomes even more complex when considering multiple animals interacting, where behavioural coupling can introduce new timescales of importance. Here, we present a technique to study the time-varying nature of social influence in mobile animal groups across multiple temporal scales. As case studies, we analyse golden shiner fish and homing pigeons, which move in different media. By analysing pairwise interactions among individuals, we show that predictive power of the factors affecting social influence depends on the timescale of analysis. Over short timescales the relative position of a neighbour best predicts its influence and the distribution of influence across group members is relatively linear, with a small slope. At longer timescales, however, both relative position and kinematics are found to predict influence, and nonlinearity in the influence distribution increases, with a small number of individuals being disproportionately influential. Our results demonstrate that different interpretations of social influence arise from analysing behaviour at different timescales, highlighting the importance of considering its multiscale nature. This article is part of a discussion meeting issue 'Collective behaviour through time'.
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Affiliation(s)
- Vivek H. Sridhar
- Department of Biology, University of Konstanz, 78464 Konstanz, Germany,Centre for the Advanced Study of Collective Behaviour, University of Konstanz, 78464 Konstanz, Germany,Department of Collective Behaviour, Max Planck Institute of Animal Behavior, 78464 Konstanz, Germany,Department for the Ecology of Animal Societies, Max Planck Institute of Animal Behavior, 78467 Konstanz, Germany
| | - Jacob D. Davidson
- Department of Biology, University of Konstanz, 78464 Konstanz, Germany,Centre for the Advanced Study of Collective Behaviour, University of Konstanz, 78464 Konstanz, Germany,Department of Collective Behaviour, Max Planck Institute of Animal Behavior, 78464 Konstanz, Germany
| | - Colin R. Twomey
- Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA,Mind Center for Outreach, Research, and Education, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Matthew M. G. Sosna
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Máté Nagy
- Department of Biology, University of Konstanz, 78464 Konstanz, Germany,Centre for the Advanced Study of Collective Behaviour, University of Konstanz, 78464 Konstanz, Germany,Department of Collective Behaviour, Max Planck Institute of Animal Behavior, 78464 Konstanz, Germany,MTA-ELTE Statistical and Biological Physics Research Group, Hungarian Academy of Sciences, Budapest 1117, Hungary,MTA-ELTE ‘Lendület’ Collective Behaviour Research Group, Hungarian Academy of Sciences, Eötvös Loránd University, Budapest 1117, Hungary,Department of Biological Physics, Eötvös Loránd University, Pázmány Péter sétány 1A, Budapest 1117, Hungary
| | - Iain D. Couzin
- Department of Biology, University of Konstanz, 78464 Konstanz, Germany,Centre for the Advanced Study of Collective Behaviour, University of Konstanz, 78464 Konstanz, Germany,Department of Collective Behaviour, Max Planck Institute of Animal Behavior, 78464 Konstanz, Germany
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12
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Koger B, Deshpande A, Kerby JT, Graving JM, Costelloe BR, Couzin ID. Quantifying the movement, behaviour and environmental context of group-living animals using drones and computer vision. J Anim Ecol 2023. [PMID: 36945122 DOI: 10.1111/1365-2656.13904] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 02/07/2023] [Indexed: 03/23/2023]
Abstract
Methods for collecting animal behaviour data in natural environments, such as direct observation and biologging, are typically limited in spatiotemporal resolution, the number of animals that can be observed and information about animals' social and physical environments. 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 geographical coordinates. We demonstrate a new system for studying behaviour 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. 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 animal trails. By quantifying animal movement and posture while 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.
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Affiliation(s)
- Benjamin Koger
- Department of Collective Behaviour, Max Planck Institute of Animal Behaviour, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
| | - Adwait Deshpande
- Department of Collective Behaviour, Max Planck Institute of Animal Behaviour, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
| | - Jeffrey T Kerby
- Aarhus Institute of Advanced Studies, Aarhus University, Aarhus, Denmark
- Neukom Institute for Computational Science, Dartmouth College, Hanover, New Hampshire, USA
- Section for Ecoinformatics and Biodiversity, Department of Biology, Aarhus University, Aarhus, Denmark
| | - Jacob M Graving
- Department of Collective Behaviour, Max Planck Institute of Animal Behaviour, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
- Advanced Research Technology Unit, Max Planck Institute of Animal Behaviour, Konstanz, Germany
| | - Blair R Costelloe
- Department of Collective Behaviour, Max Planck Institute of Animal Behaviour, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
| | - Iain D Couzin
- Department of Collective Behaviour, Max Planck Institute of Animal Behaviour, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
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13
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McKee D, Tabatabai AP. Mexican jumping beans exhibit diffusive motion. Phys Rev E 2023; 107:014609. [PMID: 36797892 DOI: 10.1103/physreve.107.014609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2022] [Accepted: 11/23/2022] [Indexed: 06/18/2023]
Abstract
Organisms across many lengthscales generate specific strategies for motion that are crucial to their survival. Here, we detail the motion of a nontraditional organism, the Mexican jumping bean, where a larva encapsulated within a seed blindly moves the seed in search of shade. Using image analysis techniques, we quantitatively describe the motion of these objects as active particles. From this experimental data, we build a computational simulation that quantitatively captures the motion of these beans. And we further evaluate the effectiveness of using the observed diffusive strategy to find shade, suggesting that the random walk is an advantageous strategy for survival.
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Affiliation(s)
- Devon McKee
- Department of Physics, Seattle University, Seattle, Washington 98122, USA
| | - A Pasha Tabatabai
- Department of Physics, Seattle University, Seattle, Washington 98122, USA
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14
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Paun I, Husmeier D, Hopcraft JGC, Masolele MM, Torney CJ. Inferring spatially varying animal movement characteristics using a hierarchical continuous-time velocity model. Ecol Lett 2022; 25:2726-2738. [PMID: 36256526 PMCID: PMC9828272 DOI: 10.1111/ele.14117] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 08/18/2022] [Accepted: 08/24/2022] [Indexed: 01/12/2023]
Abstract
Understanding the spatial dynamics of animal movement is an essential component of maintaining ecological connectivity, conserving key habitats, and mitigating the impacts of anthropogenic disturbance. Altered movement and migratory patterns are often an early warning sign of the effects of environmental disturbance, and a precursor to population declines. Here, we present a hierarchical Bayesian framework based on Gaussian processes for analysing the spatial characteristics of animal movement. At the heart of our approach is a novel covariance kernel that links the spatially varying parameters of a continuous-time velocity model with GPS locations from multiple individuals. We demonstrate the effectiveness of our framework by first applying it to a synthetic data set and then by analysing telemetry data from the Serengeti wildebeest migration. Through application of our approach, we are able to identify the key pathways of the wildebeest migration as well as revealing the impacts of environmental features on movement behaviour.
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Affiliation(s)
- Ionut Paun
- School of Mathematics and StatisticsUniversity of GlasgowGlasgowUK
| | - Dirk Husmeier
- School of Mathematics and StatisticsUniversity of GlasgowGlasgowUK
| | - J. Grant C. Hopcraft
- Institute of Biodiversity, Animal Health & Comparative MedicineUniversity of GlasgowGraham Kerr BuildingGlasgowUK
| | | | - Colin J. Torney
- School of Mathematics and StatisticsUniversity of GlasgowGlasgowUK
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15
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Detecting Changes in Dynamic Social Networks Using Multiply-Labeled Movement Data. JOURNAL OF AGRICULTURAL, BIOLOGICAL AND ENVIRONMENTAL STATISTICS 2022. [DOI: 10.1007/s13253-022-00522-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
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16
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Assessing neophobia and exploration while accounting for social context: an example application in scimitar-horned oryx. Mamm Biol 2022. [DOI: 10.1007/s42991-022-00271-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
AbstractSpatial neophobia and exploration are often assessed in nonhuman animals by measuring behavioral responses to novel environments. These traits may especially affect the performance of individuals translocated to novel environments for conservation purposes. Here, we present methods to administer and analyze a minimally invasive novel environment test that accounts for the social context of focal individuals. We used an aerial platform to capture video footage of a captive herd of scimitar-horned oryx (Oryx dammah) entering an unfamiliar enclosure. We analyzed footage for seven individually identifiable oryx, scoring their behavioral responses (i.e., latency to enter the enclosure, and movement and posture after entering the enclosure) and social context (i.e., relative position and number of nearby animals). We performed a principal components analysis (PCA) to explore individual traits and responses, and used generalized linear mixed models (GLMMs) to determine the effect of individual traits and social context on individual posture and movement behaviors. Both PCA and GLMMs supported our expectation that social context affects individual behavior: high neighbor density and relative position were negatively related to individual movement, and variation in social context was positively related with head-up postures and movement. Oryx were well differentiated along two principal components that reflected (1) vigilance or caution, and (2) changing social context and age. These methods provide a framework for assessing individual responses to a novel environment in a group setting, which can inform reintroduction and wildlife management efforts, while minimizing interference with animal behavior and management operations.
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17
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Morera‐Pujol V, Catry P, Magalhães M, Péron C, Reyes‐González JM, Granadeiro JP, Militão T, Dias MP, Oro D, Dell'Omo G, Müller M, Paiva VH, Metzger B, Neves V, Navarro J, Karris G, Xirouchakis S, Cecere JG, Zamora‐López A, Forero MG, Ouni R, Romdhane MS, De Felipe F, Zajková Z, Cruz‐Flores M, Grémillet D, González‐Solís J, Ramos R. Methods to detect spatial biases in tracking studies caused by differential representativeness of individuals, populations and time. DIVERS DISTRIB 2022. [DOI: 10.1111/ddi.13642] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
- Virginia Morera‐Pujol
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia Universitat de Barcelona (UB) Barcelona Spain
- Institut de Recerca de la Biodiversitat (IRBio) Universitat de Barcelona (UB) Barcelona Spain
| | - Paulo Catry
- MARE ‐ Marine and Environmental Sciences Centre ISPA‐Instituto Universitário Lisbon Portugal
| | - Maria Magalhães
- Regional Secretariat for the Sea, Science and Technology Regional Directorate for Sea Affairs (DRAM) Horta Portugal
| | - Clara Péron
- Laboratoire de Biologie des Organismes et Ecosystèmes Aquatiques (UMR BOREA) MNHN, CNRS, IRD, SU, UCN, UA Paris France
| | - José Manuel Reyes‐González
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia Universitat de Barcelona (UB) Barcelona Spain
- Institut de Recerca de la Biodiversitat (IRBio) Universitat de Barcelona (UB) Barcelona Spain
| | - José Pedro Granadeiro
- Departamento de Biologia Animal, CESAM, Faculdade de Ciências Universidade de Lisboa Lisboa Portugal
| | - Teresa Militão
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia Universitat de Barcelona (UB) Barcelona Spain
- Institut de Recerca de la Biodiversitat (IRBio) Universitat de Barcelona (UB) Barcelona Spain
| | - Maria P. Dias
- Centre for Ecology, Evolution and Environmental Changes (cE3c) & CHANGE (Global Change and Sustainability Institute). Departamento de Biologia Animal Faculdade de Ciências da Universidade de Lisboa Lisboa Portugal
| | - Daniel Oro
- Centre d'Estudis Avançats de Blanes (CSIC) Blanes Spain
- IMEDEA (CSIC‐UIB) Esporles Spain
| | | | - Martina Müller
- Department of Natural Resources Science University of Rhode Island Kingston Rhode Island USA
| | - Vitor H. Paiva
- Department of Life Sciences, MARE ‐ Marine and Environmental Sciences Centre/ARNET ‐ Aquatic Research Network University of Coimbra Coimbra Portugal
| | | | - Verónica Neves
- Institute of Marine Sciences ‐ Okeanos University of the Azores Horta Portugal
| | - Joan Navarro
- Institut de Ciències del Mar CSIC Barcelona Spain
| | - Georgios Karris
- Department of Environment, Faculty of Environment Ionian University Zakinthos Greece
| | - Stavros Xirouchakis
- Natural History Museum of Crete, University Campus (Knossos). School of Sciences & Engineering University of Crete Crete Greece
| | - Jacopo G. Cecere
- Area per l'Avifauna Migratrice (BIO‐AVM) Istituto Superiore per la Protezione e la Ricerca Ambientale (ISPRA) Ozzano Emilia Italy
| | - Antonio Zamora‐López
- Southeast Naturalists Association (ANSE) Murcia Spain
- Department of Zoology and Physical Anthropology University of Murcia, Espinardo Campus Murcia Spain
| | | | - Ridha Ouni
- Faculté des Sciences Mathématiques, Physiques et Naturelles de Tunis (FST), Université de Tunis El Manar Tunis Tunisia
| | | | - Fernanda De Felipe
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia Universitat de Barcelona (UB) Barcelona Spain
- Institut de Recerca de la Biodiversitat (IRBio) Universitat de Barcelona (UB) Barcelona Spain
| | - Zuzana Zajková
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia Universitat de Barcelona (UB) Barcelona Spain
- Institut de Recerca de la Biodiversitat (IRBio) Universitat de Barcelona (UB) Barcelona Spain
- Centre d'Estudis Avançats de Blanes (CSIC) Blanes Spain
| | - Marta Cruz‐Flores
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia Universitat de Barcelona (UB) Barcelona Spain
- Institut de Recerca de la Biodiversitat (IRBio) Universitat de Barcelona (UB) Barcelona Spain
| | - David Grémillet
- Centre d'Ecologie Fonctionnelle et Evolutive (CEFE), UMR 5175, CNRS, EPHE, IRD Université La Rochelle Montpellier France
- Percy Fitzpatrick Institute of African Ornithology NRF‐DST Centre of Excellence, University of Cape Town Rondebosch South Africa
| | - Jacob González‐Solís
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia Universitat de Barcelona (UB) Barcelona Spain
- Institut de Recerca de la Biodiversitat (IRBio) Universitat de Barcelona (UB) Barcelona Spain
| | - Raül Ramos
- Departament de Biologia Evolutiva, Ecologia i Ciències Ambientals, Facultat de Biologia Universitat de Barcelona (UB) Barcelona Spain
- Institut de Recerca de la Biodiversitat (IRBio) Universitat de Barcelona (UB) Barcelona Spain
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18
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Engelhardt IC, Patko D, Liu Y, Mimault M, de Las Heras Martinez G, George TS, MacDonald M, Ptashnyk M, Sukhodub T, Stanley-Wall NR, Holden N, Daniell TJ, Dupuy LX. Novel form of collective movement by soil bacteria. THE ISME JOURNAL 2022; 16:2337-2347. [PMID: 35798939 PMCID: PMC9478162 DOI: 10.1038/s41396-022-01277-w] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Revised: 06/07/2022] [Accepted: 06/17/2022] [Indexed: 04/16/2023]
Abstract
Although migrations are essential for soil microorganisms to exploit scarce and heterogeneously distributed resources, bacterial mobility in soil remains poorly studied due to experimental limitations. In this study, time-lapse images collected using live microscopy techniques captured collective and coordinated groups of B. subtilis cells exhibiting "crowd movement". Groups of B. subtilis cells moved through transparent soil (nafion polymer with particle size resembling sand) toward plant roots and re-arranged dynamically around root tips in the form of elongating and retracting "flocks" resembling collective behaviour usually associated with higher organisms (e.g., bird flocks or fish schools). Genetic analysis reveals B. subtilis flocks are likely driven by the diffusion of extracellular signalling molecules (e.g., chemotaxis, quorum sensing) and may be impacted by the physical obstacles and hydrodynamics encountered in the soil like environment. Our findings advance understanding of bacterial migration through soil matrices and expand known behaviours for coordinated bacterial movement.
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Affiliation(s)
- I C Engelhardt
- Ecological Sciences, The James Hutton Institute, Dundee, UK
- Department of Conservation of Natural Resources, Neiker, Bilbao, Spain
| | - D Patko
- Ecological Sciences, The James Hutton Institute, Dundee, UK
- Department of Conservation of Natural Resources, Neiker, Bilbao, Spain
| | - Y Liu
- Ecological Sciences, The James Hutton Institute, Dundee, UK
- ICS, The James Hutton Institute, Dundee, UK
| | - M Mimault
- ICS, The James Hutton Institute, Dundee, UK
| | | | - T S George
- Ecological Sciences, The James Hutton Institute, Dundee, UK
| | - M MacDonald
- School of Science and Engineering, University of Dundee, Dundee, UK
| | - M Ptashnyk
- School of Mathematical & Computer Sciences, Heriot-Watt University, Edinburgh, UK
| | - T Sukhodub
- School of Life Sciences, University of Dundee, Dundee, UK
| | | | - N Holden
- Ecological Sciences, The James Hutton Institute, Dundee, UK
- North Faculty, Scotland's Rural College, Aberdeen, UK
| | - T J Daniell
- Plants, Photosynthesis and Soil, School of Biosciences, The University of Sheffield, Sheffield, UK
| | - L X Dupuy
- Ecological Sciences, The James Hutton Institute, Dundee, UK.
- Department of Conservation of Natural Resources, Neiker, Bilbao, Spain.
- Ikerbasque, Basque Foundation for Science, Bilbao, Spain.
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19
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Raab T, Madhav MS, Jayakumar RP, Henninger J, Cowan NJ, Benda J. Advances in non-invasive tracking of wave-type electric fish in natural and laboratory settings. Front Integr Neurosci 2022; 16:965211. [PMID: 36118117 PMCID: PMC9478915 DOI: 10.3389/fnint.2022.965211] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2022] [Accepted: 08/10/2022] [Indexed: 11/15/2022] Open
Abstract
Recent technological advances greatly improved the possibility to study freely behaving animals in natural conditions. However, many systems still rely on animal-mounted devices, which can already bias behavioral observations. Alternatively, animal behaviors can be detected and tracked in recordings of stationary sensors, e.g., video cameras. While these approaches circumvent the influence of animal-mounted devices, identification of individuals is much more challenging. We take advantage of the individual-specific electric fields electric fish generate by discharging their electric organ (EOD) to record and track their movement and communication behaviors without interfering with the animals themselves. EODs of complete groups of fish can be recorded with electrode arrays submerged in the water and then be tracked for individual fish. Here, we present an improved algorithm for tracking electric signals of wave-type electric fish. Our algorithm benefits from combining and refining previous approaches of tracking individual specific EOD frequencies and spatial electric field properties. In this process, the similarity of signal pairs in extended data windows determines their tracking order, making the algorithm more robust against detection losses and intersections. We quantify the performance of the algorithm and show its application for a data set recorded with an array of 64 electrodes distributed over a 12 m2 section of a stream in the Llanos, Colombia, where we managed, for the first time, to track Apteronotus leptorhynchus over many days. These technological advances make electric fish a unique model system for a detailed analysis of social and communication behaviors, with strong implications for our research on sensory coding.
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Affiliation(s)
- Till Raab
- Department for Neuroethology, Institute for Neurobiology, Eberhard Karls Universität, Tübingen, Germany
- Centre for Integrative Neuroscience, Eberhard Karls Universität, Tübingen, Germany
- *Correspondence: Till Raab
| | - Manu S. Madhav
- Mind/Brain Institute, Johns Hopkins University, Baltimore, MD, United States
| | | | - Jörg Henninger
- Charité-Universitätsmedizin Berlin, Einstein Center for Neurosciences, NeuroCure Cluster of Excellence, Berlin, Germany
| | - Noah J. Cowan
- Mechanical Engineering Department, Johns Hopkins University, Baltimore, MD, United States
| | - Jan Benda
- Department for Neuroethology, Institute for Neurobiology, Eberhard Karls Universität, Tübingen, Germany
- Centre for Integrative Neuroscience, Eberhard Karls Universität, Tübingen, Germany
- Bernstein Centre for Computational Neuroscience, Eberhard Karls Universität, Tübingen, Germany
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20
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Viewing animal migration through a social lens. Trends Ecol Evol 2022; 37:985-996. [PMID: 35931583 DOI: 10.1016/j.tree.2022.06.008] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2022] [Revised: 06/03/2022] [Accepted: 06/15/2022] [Indexed: 11/22/2022]
Abstract
Evidence of social learning is growing across the animal kingdom. Researchers have long hypothesized that social interactions play a key role in many animal migrations, but strong empirical support is scarce except in a few unique systems and species. In this review, we aim to catalyze advances in the study of social migrations by synthesizing research across disciplines and providing a framework for understanding when, how, and why social influences shape the decisions animals make during migration. Integrating research across the fields of social learning and migration ecology will advance our understanding of the complex behavioral phenomena of animal migration and help to inform conservation of animal migrations in a changing world.
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21
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Schad L, Fischer J. Opportunities and risks in the use of drones for studying animal behaviour. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13922] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Lukas Schad
- Cognitive Ethology Laboratory German Primate Center Göttingen Germany
- Leibniz ScienceCampus Primate Cognition Göttingen Germany
| | - Julia Fischer
- Cognitive Ethology Laboratory German Primate Center Göttingen Germany
- Leibniz ScienceCampus Primate Cognition Göttingen Germany
- Department for Primate Cognition Georg‐August‐University Göttingen Göttingen Germany
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22
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Doherty CTM, Laidre ME. Individualism versus collective movement during travel. Sci Rep 2022; 12:7508. [PMID: 35525848 PMCID: PMC9079110 DOI: 10.1038/s41598-022-11469-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Accepted: 04/22/2022] [Indexed: 11/24/2022] Open
Abstract
Collective movement may emerge if coordinating one’s movement with others produces a greater benefit to oneself than can be achieved alone. Experimentally, the capacity to manoeuvre simulated groups in the wild could enable powerful tests of the impact of collective movement on individual decisions. Yet such experiments are currently lacking due to the inherent difficulty of controlling whole collectives. Here we used a novel technique of experimentally simulating the movement of collectives of social hermit crabs (Coenobita compressus) in the wild. Using large architectural arrays of shells dragged across the beach, we generated synchronous collective movement and systematically varied the simulated collective’s travel direction as well as the context (i.e., danger level). With drone video from above, we then tested whether focal individuals were biased in their movement by the collective. We found that, despite considerable engagement with the collective, individuals’ direction was not significantly biased. Instead, individuals expressed substantial variability across all stimulus directions and contexts. Notably, individuals typically achieved shorter displacements in the presence of the collective versus in the presence of the control stimulus, suggesting an impact of traffic. The absence of a directional bias in individual movement due to the collective suggests that social hermit crabs are individualists, which move with a high level of opportunistic independence, likely thanks to the personal architecture and armour they carry in the form of a protective shell. Future studies can manipulate this level of armour to test its role in autonomy of movement, including the consequences of shell architecture for social decisions. Our novel experimental approach can be used to ask many further questions about how and why collective and individual movement interact.
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Affiliation(s)
- Clare T M Doherty
- Department of Biological Sciences, Dartmouth College, 78 College Street, Hanover, NH, 03755, USA. .,Graduate Program in Ecology, Evolution, Environment, and Society, Dartmouth College, Hanover, NH, 03755, USA.
| | - Mark E Laidre
- Department of Biological Sciences, Dartmouth College, 78 College Street, Hanover, NH, 03755, USA. .,Graduate Program in Ecology, Evolution, Environment, and Society, Dartmouth College, Hanover, NH, 03755, USA.
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23
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Abstract
The development of ecotourism involving wild animals in Russia is overlooked despite the fact that the country’s territory is significant not only in terms of area but also in terms of the diversity of its flora and fauna. A significant part of Russia’s territory has a low population density, especially beyond the Ural ridge. It retains its natural primeval nature, which can contribute to the development of ecotourism. Initial attempts have been made to develop this, mainly in the European part (Tatarstan, Murmansk Region, the Baltic Sea, Baikal, Altai), but the commercial use of wild animals within ecotourism programs, including the ones in Siberia and the Far East, has not been discussed. This work focuses on the basics of launching ecotourism in the industrial region of Siberia (Kuzbass, Russia) as part of the Alcesalces conservation program.
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24
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Studying feral horse behavior from the sky. ARTIFICIAL LIFE AND ROBOTICS 2022. [DOI: 10.1007/s10015-022-00746-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
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25
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Sattari S, Basak US, James RG, Perrin LW, Crutchfield JP, Komatsuzaki T. Modes of information flow in collective cohesion. SCIENCE ADVANCES 2022; 8:eabj1720. [PMID: 35138896 PMCID: PMC8827646 DOI: 10.1126/sciadv.abj1720] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/25/2021] [Accepted: 12/20/2021] [Indexed: 05/23/2023]
Abstract
Pairwise interactions are fundamental drivers of collective behavior-responsible for group cohesion. The abiding question is how each individual influences the collective. However, time-delayed mutual information and transfer entropy, commonly used to quantify mutual influence in aggregated individuals, can result in misleading interpretations. Here, we show that these information measures have substantial pitfalls in measuring information flow between agents from their trajectories. We decompose the information measures into three distinct modes of information flow to expose the role of individual and group memory in collective behavior. It is found that decomposed information modes between a single pair of agents reveal the nature of mutual influence involving many-body nonadditive interactions without conditioning on additional agents. The pairwise decomposed modes of information flow facilitate an improved diagnosis of mutual influence in collectives.
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Affiliation(s)
- Sulimon Sattari
- Research Center of Mathematics for Social Creativity, Research Institute for Electronic Science, Hokkaido University Kita 20, Nishi 10, Kita-ku, Sapporo, Hokkaido 001-0020, Japan
| | - Udoy S. Basak
- Research Center of Mathematics for Social Creativity, Research Institute for Electronic Science, Hokkaido University Kita 20, Nishi 10, Kita-ku, Sapporo, Hokkaido 001-0020, Japan
- Pabna University of Science and Technology, Pabna 6600, Bangladesh
| | - Ryan G. James
- Reddit Inc., 420 Taylor Street, San Francisco, CA 94102, USA
- Department of Physics, Complexity Sciences Center, University of California, Davis, Davis, CA 95616, USA
| | - Louis W. Perrin
- Research Center of Mathematics for Social Creativity, Research Institute for Electronic Science, Hokkaido University Kita 20, Nishi 10, Kita-ku, Sapporo, Hokkaido 001-0020, Japan
- École Normale Supérieure de Rennes, Robert Schumann, Campus de, Av. de Ker Lann, 35170 Bruz, France
| | - James P. Crutchfield
- Department of Physics, Complexity Sciences Center, University of California, Davis, Davis, CA 95616, USA
| | - Tamiki Komatsuzaki
- Research Center of Mathematics for Social Creativity, Research Institute for Electronic Science, Hokkaido University Kita 20, Nishi 10, Kita-ku, Sapporo, Hokkaido 001-0020, Japan
- Institute for Chemical Reaction Design and Discovery (WPI-ICReDD), Hokkaido University Kita 21 Nishi 10, Kita-ku, Sapporo, Hokkaido 001-0021, Japan
- Graduate School of Chemical Sciences and Engineering Materials Chemistry and Energy Course, Hokkaido University Kita 13, Nishi 8, Kita-ku Sapporo, Hokkaido 060-0812, Japan
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26
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Joly K, Gunn A, Côté SD, Panzacchi M, Adamczewski J, Suitor MJ, Gurarie E. Caribou and reindeer migrations in the changing Arctic. ANIMAL MIGRATION 2021. [DOI: 10.1515/ami-2020-0110] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
Abstract
Caribou and reindeer, Rangifer tarandus, are the most numerous and socio-ecologically important terrestrial species in the Arctic. Their migrations are directly and indirectly affected by the seasonal nature of the northernmost regions, human development and population size; all of which are impacted by climate change. We review the most critical drivers of Rangifer migration and how a rapidly changing Arctic may affect them. In order to conserve large Rangifer populations, they must be allowed free passage along their migratory routes to reach seasonal ranges. We also provide some pragmatic ideas to help conserve Rangifer migrations into the future.
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Affiliation(s)
- Kyle Joly
- Gates of the Arctic National Park and Preserve, Arctic Inventory and Monitoring Network, National Park Service , 4175 Geist Road, Fairbanks, Alaska, 99709, USA
| | - Anne Gunn
- Salt Spring Island , British Columbia V8K 1V1 Canada
| | - Steeve D. Côté
- Département de biologie, Caribou Ungava & Centre d’études nordiques , Université Laval , Québec (QC), G1V 0A6 , Canada
| | - Manuela Panzacchi
- Norwegian Institute for Nature Research (NINA) , Høgskoleringen 9, NO-7034 Trondheim , Norway
| | - Jan Adamczewski
- Department of Environment and Natural Resources, Government of the Northwest Territories , Yellowknife, Northwest Territories , Canada
| | - Michael J. Suitor
- Fish and Wildlife Branch, Environment Yukon, Yukon Government , Dawson City , Yukon , Canada
| | - Eliezer Gurarie
- Department of Biology , University of Maryland , College Park, Maryland, 20742, USA , and Department of Environmental and Forest Biology, SUNY College of Environmental Science and Forestry , Syracuse , NY 13210
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27
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Maeda T, Sueur C, Hirata S, Yamamoto S. Behavioural synchronization in a multilevel society of feral horses. PLoS One 2021; 16:e0258944. [PMID: 34699556 PMCID: PMC8547633 DOI: 10.1371/journal.pone.0258944] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Accepted: 10/06/2021] [Indexed: 11/26/2022] Open
Abstract
Behavioural synchrony among individuals is essential for group-living organisms. The functioning of synchronization in a multilevel society, which is a nested assemblage of multiple social levels between many individuals, remains largely unknown. The aim of the present study was to build a model that explained the synchronization of activity in a multilevel society of feral horses. Multi-agent-based models were used based on four hypotheses: A) horses do not synchronize, B) horses synchronize with any individual in any unit, C) horses synchronize only within units, and D) horses synchronize across and within units, but internal synchronization is stronger. The empirical data obtained from drone observations best supported hypothesis D. This result suggests that animals in a multilevel society coordinate with other conspecifics not only within a unit but also at an inter-unit level. In this case, inter-individual distances are much longer than those in most previous models which only considered local interaction within a few body lengths.
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Affiliation(s)
- Tamao Maeda
- Wildlife Research Centre, Kyoto University, Kyoto, Japan
- * E-mail:
| | - Cédric Sueur
- Institut Pluridisciplinaire Hubert Curien, Université de Strasbourg, CNRS, Strasbourg, France
- Institut Universitaire de France, Paris, France
| | - Satoshi Hirata
- Wildlife Research Centre, Kyoto University, Kyoto, Japan
| | - Shinya Yamamoto
- Wildlife Research Centre, Kyoto University, Kyoto, Japan
- Institute for Advanced Study, Kyoto University, Kyoto, Japan
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Abstract
Collective migration occurs throughout the animal kingdom, and demands both the interpretation of navigational cues and the perception of other individuals within the group. Navigational cues orient individuals towards a destination, while it has been demonstrated that communication between individuals enhances navigation through a reduction in orientation error. We develop a mathematical model of collective navigation that synthesizes navigational cues and perception of other individuals. Crucially, this approach incorporates uncertainty inherent to cue interpretation and perception in the decision making process, which can arise due to noisy environments. We demonstrate that collective navigation is more efficient than individual navigation, provided a threshold number of other individuals are perceptible. This benefit is even more pronounced in low navigation information environments. In navigation ‘blindspots’, where no information is available, navigation is enhanced through a relay that connects individuals in information-poor regions to individuals in information-rich regions. As an expository case study, we apply our framework to minke whale migration in the northeast Atlantic Ocean, and quantify the decrease in navigation ability due to anthropogenic noise pollution.
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Affiliation(s)
- S T Johnston
- Systems Biology Laboratory, School of Mathematics and Statistics, and Department of Biomedical Engineering, University of Melbourne, Parkville, Victoria 3010, Australia
| | - K J Painter
- Dipartimento Interateneo di Scienze, Progetto e Politiche del Territorio (DIST) Politecnico di Torino, Viale Pier Andrea Mattioli, Torino 39 10125, Italy
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Georgopoulou DG, King AJ, Brown RM, Fürtbauer I. Emergence and repeatability of leadership and coordinated motion in fish shoals. Behav Ecol 2021; 33:47-54. [PMID: 35197806 PMCID: PMC8857939 DOI: 10.1093/beheco/arab108] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2021] [Revised: 08/02/2021] [Accepted: 09/07/2021] [Indexed: 12/04/2022] Open
Abstract
Studies of self-organizing groups like schools of fish or flocks of birds have sought to uncover the behavioral rules individuals use (local-level interactions) to coordinate their motion (global-level patterns). However, empirical studies tend to focus on short-term or one-off observations where coordination has already been established or describe transitions between different coordinated states. As a result, we have a poor understanding of how behavioral rules develop and are maintained in groups. Here, we study the emergence and repeatability of coordinated motion in shoals of stickleback fish (Gasterosteus aculeatus). Shoals were introduced to a simple environment, where their spatio-temporal position was deduced via video analysis. Using directional correlation between fish velocities and wavelet analysis of fish positions, we demonstrate how shoals that are initially uncoordinated in their motion quickly transition to a coordinated state with defined individual leader-follower roles. The identities of leaders and followers were repeatable across two trials, and coordination was reached more quickly during the second trial and by groups of fish with higher activity levels (tested before trials). The rapid emergence of coordinated motion and repeatability of social roles in stickleback fish shoals may act to reduce uncertainty of social interactions in the wild, where individuals live in a system with high fission-fusion dynamics and non-random patterns of association.
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Affiliation(s)
- Dimitra G Georgopoulou
- College of Engineering, Swansea University, SA1 8EN Swansea, UK
- Department of Biosciences, College of Science, Swansea University, SA2 8PP Swansea, UK
| | - Andrew J King
- Department of Biosciences, College of Science, Swansea University, SA2 8PP Swansea, UK
| | - Rowan M Brown
- College of Engineering, Swansea University, SA1 8EN Swansea, UK
| | - Ines Fürtbauer
- Department of Biosciences, College of Science, Swansea University, SA2 8PP Swansea, UK
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Kashetsky T, Avgar T, Dukas R. The Cognitive Ecology of Animal Movement: Evidence From Birds and Mammals. Front Ecol Evol 2021. [DOI: 10.3389/fevo.2021.724887] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Cognition, defined as the processes concerned with the acquisition, retention and use of information, underlies animals’ abilities to navigate their local surroundings, embark on long-distance seasonal migrations, and socially learn information relevant to movement. Hence, in order to fully understand and predict animal movement, researchers must know the cognitive mechanisms that generate such movement. Work on a few model systems indicates that most animals possess excellent spatial learning and memory abilities, meaning that they can acquire and later recall information about distances and directions among relevant objects. Similarly, field work on several species has revealed some of the mechanisms that enable them to navigate over distances of up to several thousand kilometers. Key behaviors related to movement such as the choice of nest location, home range location and migration route are often affected by parents and other conspecifics. In some species, such social influence leads to the formation of aggregations, which in turn may lead to further social learning about food locations or other resources. Throughout the review, we note a variety of topics at the interface of cognition and movement that invite further investigation. These include the use of social information embedded in trails, the likely important roles of soundscapes and smellscapes, the mechanisms that large mammals rely on for long-distance migration, and the effects of expertise acquired over extended periods.
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Kumar V, De R. Efficient flocking: metric versus topological interactions. ROYAL SOCIETY OPEN SCIENCE 2021; 8:202158. [PMID: 34631117 PMCID: PMC8479340 DOI: 10.1098/rsos.202158] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/04/2020] [Accepted: 09/10/2021] [Indexed: 05/26/2023]
Abstract
Flocking is a fascinating phenomenon observed across a wide range of living organisms. We investigate, based on a simple self-propelled particle model, how the emergence of ordered motion in a collectively moving group is influenced by the local rules of interactions among the individuals, namely, metric versus topological interactions as debated in the current literature. In the case of the metric ruling, the individuals interact with the neighbours within a certain metric distance; by contrast, in the topological ruling, interaction is confined within a number of fixed nearest neighbours. Here, we explore how the range of interaction versus the number of fixed interacting neighbours affects the dynamics of flocking in an unbounded space, as observed in natural scenarios. Our study reveals the existence of a certain threshold value of the interaction radius in the case of metric ruling and a threshold number of interacting neighbours for the topological ruling to reach an ordered state. Interestingly, our analysis shows that topological interaction is more effective in bringing the order in the group, as observed in field studies. We further compare how the nature of the interactions affects the dynamics for various sizes and speeds of the flock.
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Affiliation(s)
- Vijay Kumar
- Department of Physical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur 741246, West Bengal, India
- Centre for Computational and Data-Intensive Science and Engineering, Skolkovo Institute of Science and Technology, Nobelya Ulitsa 3, Moscow, 121205, Russia
| | - Rumi De
- Department of Physical Sciences, Indian Institute of Science Education and Research Kolkata, Mohanpur 741246, West Bengal, India
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Dalziel BD, Novak M, Watson JR, Ellner SP. Collective behaviour can stabilize ecosystems. Nat Ecol Evol 2021; 5:1435-1440. [PMID: 34385617 DOI: 10.1038/s41559-021-01517-w] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Accepted: 06/18/2021] [Indexed: 11/09/2022]
Abstract
Collective behaviour is common in bacteria, plants and animals, and therefore occurs across ecosystems, from biofilms to cities. With collective behaviour, social interactions among individuals propagate to affect the behaviour of groups, whereas group-level responses in turn affect individual behaviour. These cross-scale feedback loops between individuals, populations and their environments can provide fitness benefits, such as the efficient exploitation of uncertain resources, as well as costs, such as increased resource competition. Although the social mechanics of collective behaviour are increasingly well-studied, its role in ecosystems remains poorly understood. Here we introduce collective movement into a model of consumer-resource dynamics to demonstrate that collective behaviour can attenuate consumer-resource cycles and promote species coexistence. We focus on collective movement as a particularly well-understood example of collective behaviour. Adding collective movement to canonical unstable ecological scenarios causes emergent social-ecological feedback, which mitigates conditions that would otherwise result in extinction. Collective behaviour could play a key part in the maintenance of biodiversity.
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Affiliation(s)
- Benjamin D Dalziel
- Department of Integrative Biology, Oregon State University, Corvallis, OR, USA. .,Department of Mathematics, Oregon State University, Corvallis, OR, USA.
| | - Mark Novak
- Department of Integrative Biology, Oregon State University, Corvallis, OR, USA
| | - James R Watson
- College of Earth, Ocean and Atmospheric Sciences, Oregon State University, Corvallis, OR, USA
| | - Stephen P Ellner
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA
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Davidson JD, Sosna MMG, Twomey CR, Sridhar VH, Leblanc SP, Couzin ID. Collective detection based on visual information in animal groups. J R Soc Interface 2021; 18:20210142. [PMID: 34229461 PMCID: PMC8261228 DOI: 10.1098/rsif.2021.0142] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2021] [Accepted: 06/10/2021] [Indexed: 01/14/2023] Open
Abstract
We investigate key principles underlying individual, and collective, visual detection of stimuli, and how this relates to the internal structure of groups. While the individual and collective detection principles are generally applicable, we employ a model experimental system of schooling golden shiner fish (Notemigonus crysoleucas) to relate theory directly to empirical data, using computational reconstruction of the visual fields of all individuals. This reveals how the external visual information available to each group member depends on the number of individuals in the group, the position within the group, and the location of the external visually detectable stimulus. We find that in small groups, individuals have detection capability in nearly all directions, while in large groups, occlusion by neighbours causes detection capability to vary with position within the group. To understand the principles that drive detection in groups, we formulate a simple, and generally applicable, model that captures how visual detection properties emerge due to geometric scaling of the space occupied by the group and occlusion caused by neighbours. We employ these insights to discuss principles that extend beyond our specific system, such as how collective detection depends on individual body shape, and the size and structure of the group.
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Affiliation(s)
- Jacob D. Davidson
- Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
| | - Matthew M. G. Sosna
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Colin R. Twomey
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA
- Mind Center for Outreach, Research, and Education, University of Pennsylvania, Philadelphia, PA, USA
| | - Vivek H. Sridhar
- Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
| | - Simon P. Leblanc
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Iain D. Couzin
- Department of Collective Behaviour, Max Planck Institute of Animal Behavior, Konstanz, Germany
- Centre for the Advanced Study of Collective Behaviour, University of Konstanz, Konstanz, Germany
- Department of Biology, University of Konstanz, Konstanz, Germany
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Mann RP. Optimal use of simplified social information in sequential decision-making. J R Soc Interface 2021; 18:20210082. [PMID: 34062101 DOI: 10.1098/rsif.2021.0082] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Social animals can improve their decisions by attending to those made by others. The benefit of this social information must be balanced against the costs of obtaining and processing it. Previous work has focused on rational agents that respond optimally to a sequence of prior decisions. However, full decision sequences are potentially costly to perceive and process. As such, animals may rely on simpler social information, which will affect the social behaviour they exhibit. Here, I derive the optimal policy for agents responding to simplified forms of social information. I show how the behaviour of agents attending to the aggregate number of previous choices differs from those attending to just the most recent prior decision, and I propose a hybrid strategy that provides a highly accurate approximation to the optimal policy with the full sequence. Finally, I analyse the evolutionary stability of each strategy, showing that the hybrid strategy dominates when cognitive costs are low but non-zero, while attending to the most recent decision is dominant when costs are high. These results show that agents can employ highly effective social decision-making rules without requiring unrealistic cognitive capacities, and indicate likely ecological variation in the social information different animals attend to.
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Affiliation(s)
- Richard P Mann
- Department of Statistics, School of Mathematics, University of Leeds, Leeds, UK
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35
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Joly K, Gurarie E, Hansen DA, Cameron MD. Seasonal patterns of spatial fidelity and temporal consistency in the distribution and movements of a migratory ungulate. Ecol Evol 2021; 11:8183-8200. [PMID: 34188879 PMCID: PMC8216956 DOI: 10.1002/ece3.7650] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2020] [Revised: 04/19/2021] [Accepted: 04/21/2021] [Indexed: 11/06/2022] Open
Abstract
How animals use their range can have physiological, ecological, and demographic repercussions, as well as impact management decisions, species conservation, and human society. Fidelity, the predictable return to certain places, can improve fitness if it is associated with high-quality habitat or helps enable individuals to locate heterogenous patches of higher-quality habitat within a lower-quality habitat matrix. Our goal was to quantify patterns of fidelity at different spatial scales to better understand the relative plasticity of habitat use of a vital subsistence species that undergoes long-distance migrations. We analyzed a decade (2010-2019) of GPS data from 240 adult, female Western Arctic Herd (WAH) caribou (Rangifer tarandus) from northwest Alaska, U.S.A. We assessed fidelity at 2 spatial scales: to site-specific locations within seasonal ranges and to regions within the herd's entire range by using 2 different null datasets. We assessed both area and consistency of use during 6 different seasons of the year. We also assessed the temporal consistency of migration and calving events. At the scale of the overall range, we found that caribou fidelity was greatest during the calving and insect relief (early summer) seasons, where the herd tended to maximally aggregate in the smallest area, and lowest in winter when the seasonal range is largest. However, even in seasons with lower fidelity, we found that caribou still showed fidelity to certain regions within the herd's range. Within those seasonal ranges, however, there was little individual site-specific fidelity from year to year, with the exception of summer periods. Temporally, we found that over 90% of caribou gave birth within 7 days of the day they gave birth the previous year. This revealed fairly high temporal consistency, especially given the spatial and temporal variability of spring migration. Fall migration exhibited greater temporal variability than spring migration. Our results support the hypothesis that higher fidelity to seasonal ranges is related to greater environmental and resource predictability. Interestingly, this fidelity was stronger at larger scales and at the population level. Almost the entire herd would seek out these areas with predictable resources, and then, individuals would vary their use, likely in response to annually varying conditions. During seasons with lower presumed spatial and/or temporal predictability of resources, population-level fidelity was lower but individual fidelity was higher. The herd would be more spread out during the seasons of low-resource predictability, leading to lower fidelity at the scale of their entire range, but individuals could be closer to locations they used the previous year, leading to greater individual fidelity, perhaps resulting from memory of a successful outcome the previous year. Our results also suggest that fidelity in 1 season is related to fidelity in the subsequent season. We hypothesize that some differences in patterns of range fidelity may be driven by seasonal differences in group size, degree of sociality, and/or density-dependent factors. Climate change may affect resource predictability and, thus, the spatial fidelity and temporal consistency of use of animals to certain seasonal ranges.
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Affiliation(s)
- Kyle Joly
- Gates of the Arctic National Park and PreserveArctic Inventory and Monitoring NetworkNational Park ServiceFairbanksAKUSA
| | - Eliezer Gurarie
- Department of BiologyUniversity of MarylandCollege ParkMDUSA
| | - D. Alexander Hansen
- Division of Wildlife ConservationAlaska Department of Fish and GameKotzebueAKUSA
| | - Matthew D. Cameron
- Gates of the Arctic National Park and PreserveArctic Inventory and Monitoring NetworkNational Park ServiceFairbanksAKUSA
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Animal Welfare Implications of Digital Tools for Monitoring and Management of Cattle and Sheep on Pasture. Animals (Basel) 2021; 11:ani11030829. [PMID: 33804235 PMCID: PMC8000582 DOI: 10.3390/ani11030829] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 03/04/2021] [Accepted: 03/05/2021] [Indexed: 02/05/2023] Open
Abstract
Simple Summary Monitoring the welfare of cattle and sheep in large pastures can be time-consuming, especially if the animals are scattered over large areas in semi-natural pastures. There are several technologies for monitoring animals with wearable or remote equipment for recording physiological or behavioural parameters and trigger alarms when the acquired information deviates from the normal. Automatic equipment allows continuous monitoring and may give more information than manual monitoring. Ear tags with electronic identification can detect visits to specific points. Collars with positioning (GPS) units can assess the animals’ movements and habitat selection and, to some extent, their health and welfare. Digitally determined virtual fences, instead of the traditional physical ones, have the potential to keep livestock within a predefined area using audio signals in combination with weak electric shocks, although some individuals may have difficulties in responding as intended, potentially resulting in reduced animal welfare. Remote technology such as drones equipped with cameras can be used to count animals, determine their position and study their behaviour. Drones can also herd and move animals. However, the knowledge of the potential effects on animal welfare of digital technology for monitoring and managing grazing livestock is limited, especially regarding drones and virtual fences. Abstract The opportunities for natural animal behaviours in pastures imply animal welfare benefits. Nevertheless, monitoring the animals can be challenging. The use of sensors, cameras, positioning equipment and unmanned aerial vehicles in large pastures has the potential to improve animal welfare surveillance. Directly or indirectly, sensors measure environmental factors together with the behaviour and physiological state of the animal, and deviations can trigger alarms for, e.g., disease, heat stress and imminent calving. Electronic positioning includes Radio Frequency Identification (RFID) for the recording of animals at fixed points. Positioning units (GPS) mounted on collars can determine animal movements over large areas, determine their habitat and, somewhat, health and welfare. In combination with other sensors, such units can give information that helps to evaluate the welfare of free-ranging animals. Drones equipped with cameras can also locate and count the animals, as well as herd them. Digitally defined virtual fences can keep animals within a predefined area without the use of physical barriers, relying on acoustic signals and weak electric shocks. Due to individual variations in learning ability, some individuals may be exposed to numerous electric shocks, which might compromise their welfare. More research and development are required, especially regarding the use of drones and virtual fences.
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de Guinea M, Estrada A, Janmaat KR, Nekaris KAI, Van Belle S. Disentangling the importance of social and ecological information in goal-directed movements in a wild primate. Anim Behav 2021. [DOI: 10.1016/j.anbehav.2020.12.017] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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Torney CJ, Morales JM, Husmeier D. A hierarchical machine learning framework for the analysis of large scale animal movement data. MOVEMENT ECOLOGY 2021; 9:6. [PMID: 33602302 PMCID: PMC7893961 DOI: 10.1186/s40462-021-00242-0] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/17/2020] [Accepted: 01/27/2021] [Indexed: 06/12/2023]
Abstract
BACKGROUND In recent years the field of movement ecology has been revolutionized by our ability to collect high-accuracy, fine scale telemetry data from individual animals and groups. This growth in our data collection capacity has led to the development of statistical techniques that integrate telemetry data with random walk models to infer key parameters of the movement dynamics. While much progress has been made in the use of these models, several challenges remain. Notably robust and scalable methods are required for quantifying parameter uncertainty, coping with intermittent location fixes, and analysing the very large volumes of data being generated. METHODS In this work we implement a novel approach to movement modelling through the use of multilevel Gaussian processes. The hierarchical structure of the method enables the inference of continuous latent behavioural states underlying movement processes. For efficient inference on large data sets, we approximate the full likelihood using trajectory segmentation and sample from posterior distributions using gradient-based Markov chain Monte Carlo methods. RESULTS While formally equivalent to many continuous-time movement models, our Gaussian process approach provides flexible, powerful models that can detect multiscale patterns and trends in movement trajectory data. We illustrate a further advantage to our approach in that inference can be performed using highly efficient, GPU-accelerated machine learning libraries. CONCLUSIONS Multilevel Gaussian process models offer efficient inference for large-volume movement data sets, along with the fitting of complex flexible models. Applications of this approach include inferring the mean location of a migration route and quantifying significant changes, detecting diurnal activity patterns, or identifying the onset of directed persistent movements.
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Affiliation(s)
- Colin J Torney
- School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8SQ, UK.
| | - Juan M Morales
- School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8SQ, UK
- Grupo de Ecología Cuantitativa, INIBIOMA, Universidad Nacional del Comahue, CONICET, Düsternbrooker Weg 20, Bariloche, S4140, Argentina
| | - Dirk Husmeier
- School of Mathematics and Statistics, University of Glasgow, Glasgow, G12 8SQ, UK
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Abstract
Over the past decade, drones have become a popular tool for wildlife management and research. Drones have shown significant value for animals that were often difficult or dangerous to study using traditional survey methods. In the past five years drone technology has become commonplace for shark research with their use above, and more recently, below the water helping to minimise knowledge gaps about these cryptic species. Drones have enhanced our understanding of shark behaviour and are critically important tools, not only due to the importance and conservation of the animals in the ecosystem, but to also help minimise dangerous encounters with humans. To provide some guidance for their future use in relation to sharks, this review provides an overview of how drones are currently used with critical context for shark monitoring. We show how drones have been used to fill knowledge gaps around fundamental shark behaviours or movements, social interactions, and predation across multiple species and scenarios. We further detail the advancement in technology across sensors, automation, and artificial intelligence that are improving our abilities in data collection and analysis and opening opportunities for shark-related beach safety. An investigation of the shark-based research potential for underwater drones (ROV/AUV) is also provided. Finally, this review provides baseline observations that have been pioneered for shark research and recommendations for how drones might be used to enhance our knowledge in the future.
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Maeda T, Ochi S, Ringhofer M, Sosa S, Sueur C, Hirata S, Yamamoto S. Aerial drone observations identified a multilevel society in feral horses. Sci Rep 2021; 11:71. [PMID: 33420148 PMCID: PMC7794487 DOI: 10.1038/s41598-020-79790-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 12/14/2020] [Indexed: 12/14/2022] Open
Abstract
The study of non-human multilevel societies can give us insights into how group-level relationships function and are maintained in a social system, but their mechanisms are still poorly understood. The aim of this study was to apply spatial association data obtained from drones to verify the presence of a multilevel structure in a feral horse society. We took aerial photos of individuals that appeared in pre-fixed areas and collected positional data. The threshold distance of the association was defined based on the distribution pattern of the inter-individual distance. The association rates of individuals showed bimodality, suggesting the presence of small social organizations or "units". Inter-unit distances were significantly smaller than those in randomly replaced data, which showed that units associate to form a higher-level social organization or "herd". Moreover, this herd had a structure where large mixed-sex units were more likely to occupy the center than small mixed-sex units and all-male-units, which were instead on the periphery. These three pieces of evidence regarding the existence of units, unit association, and stable positioning among units strongly indicated a multilevel structure in horse society. The present study contributes to understanding the functions and mechanisms of multilevel societies through comparisons with other social indices and models as well as cross-species comparisons in future studies.
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Affiliation(s)
- Tamao Maeda
- Wildlife Research Centre, Kyoto University, 2-24 Tanaka-Sekiden-cho, Sakyo, Kyoto, Japan.
| | - Sakiho Ochi
- Wildlife Research Centre, Kyoto University, 2-24 Tanaka-Sekiden-cho, Sakyo, Kyoto, Japan
| | - Monamie Ringhofer
- Institute for Advanced Study, Kyoto University, Yoshida Ushinomiya-cho, Sakyo, Kyoto, Japan
| | - Sebastian Sosa
- Université de Strasbourg, CNRS, IPHC, UMR 7178, Strasbourg, France
| | - Cédric Sueur
- Université de Strasbourg, CNRS, IPHC, UMR 7178, Strasbourg, France
- Institut Universitaire de France, Paris, France
| | - Satoshi Hirata
- Wildlife Research Centre, Kyoto University, 2-24 Tanaka-Sekiden-cho, Sakyo, Kyoto, Japan
| | - Shinya Yamamoto
- Institute for Advanced Study, Kyoto University, Yoshida Ushinomiya-cho, Sakyo, Kyoto, Japan.
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Prichard AK, Parrett LS, Lenart EA, Caikoski JR, Joly K, Person BT. Interchange and Overlap Among Four Adjacent Arctic Caribou Herds. J Wildl Manage 2020. [DOI: 10.1002/jwmg.21934] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
| | - Lincoln S. Parrett
- Alaska Department of Fish and Game 1300 College Road Fairbanks AK 99701 USA
| | | | - Jason R. Caikoski
- Alaska Department of Fish and Game 1300 College Road Fairbanks AK 99701 USA
| | - Kyle Joly
- National Park Service, Gates of the Arctic National Park and Preserve, Arctic Inventory and Monitoring Network 4175 Geist Road Fairbanks AK 99709 USA
| | - Brian T. Person
- North Slope Borough Department of Wildlife Management P.O. Box 69 Utqiaġvik AK 99723 USA
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Escobedo R, Lecheval V, Papaspyros V, Bonnet F, Mondada F, Sire C, Theraulaz G. A data-driven method for reconstructing and modelling social interactions in moving animal groups. Philos Trans R Soc Lond B Biol Sci 2020; 375:20190380. [PMID: 32713309 DOI: 10.1098/rstb.2019.0380] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Group-living organisms that collectively migrate range from cells and bacteria to human crowds, and include swarms of insects, schools of fish, and flocks of birds or ungulates. Unveiling the behavioural and cognitive mechanisms by which these groups coordinate their movements is a challenging task. These mechanisms take place at the individual scale and can be described as a combination of interactions between individuals and interactions between these individuals and the physical obstacles in the environment. Thanks to the development of novel tracking techniques that provide large and accurate datasets, the main characteristics of individual and collective behavioural patterns can be quantified with an unprecedented level of precision. However, in a large number of studies, social interactions are usually described by force map methods that only have a limited capacity of explanation and prediction, being rarely suitable for a direct implementation in a concise and explicit mathematical model. Here, we present a general method to extract the interactions between individuals that are involved in the coordination of collective movements in groups of organisms. We then apply this method to characterize social interactions in two species of shoaling fish, the rummy-nose tetra (Hemigrammus rhodostomus) and the zebrafish (Danio rerio), which both present a burst-and-coast motion. From the detailed quantitative description of individual-level interactions, it is thus possible to develop a quantitative model of the emergent dynamics observed at the group level, whose predictions can be checked against experimental results. This method can be applied to a wide range of biological and social systems. This article is part of the theme issue 'Multi-scale analysis and modelling of collective migration in biological systems'.
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Affiliation(s)
- R Escobedo
- Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse - Paul Sabatier, 31062 Toulouse, France
| | - V Lecheval
- Department of Biology, University of York, York YO10 5DD, UK
| | - V Papaspyros
- MOBOTS group, Biorobotics laboratory, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - F Bonnet
- MOBOTS group, Biorobotics laboratory, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - F Mondada
- MOBOTS group, Biorobotics laboratory, École Polytechnique Fédérale de Lausanne, 1015 Lausanne, Switzerland
| | - C Sire
- Laboratoire de Physique Théorique, Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse - Paul Sabatier, 31062 Toulouse, France
| | - G Theraulaz
- Centre de Recherches sur la Cognition Animale, Centre de Biologie Intégrative (CBI), Centre National de la Recherche Scientifique (CNRS) & Université de Toulouse - Paul Sabatier, 31062 Toulouse, France.,Centre for Ecological Sciences, Indian Institute of Science, Bengaluru, India
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44
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Twomey CR, Hartnett AT, Sosna MMG, Romanczuk P. Searching for structure in collective systems. Theory Biosci 2020; 140:361-377. [PMID: 32206979 PMCID: PMC8629805 DOI: 10.1007/s12064-020-00311-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2018] [Accepted: 02/20/2020] [Indexed: 11/24/2022]
Abstract
From fish schools and bird flocks to biofilms and neural networks, collective systems in nature are made up of many mutually influencing individuals that interact locally to produce large-scale coordinated behavior. Although coordination is central to what it means to behave collectively, measures of large-scale coordination in these systems are ad hoc and system specific. The lack of a common quantitative scale makes broad cross-system comparisons difficult. Here we identify a system-independent measure of coordination based on an information-theoretic measure of multivariate dependence and show it can be used in practice to give a new view of even classic, well-studied collective systems. Moreover, we use this measure to derive a novel method for finding the most coordinated components within a system and demonstrate how this can be used in practice to reveal intrasystem organizational structure.
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Affiliation(s)
- Colin R Twomey
- Department of Biology, University of Pennsylvania, Philadelphia, PA, USA.
| | | | - Matthew M G Sosna
- Department of Ecology and Evolutionary Biology, Princeton University, Princeton, NJ, USA
| | - Pawel Romanczuk
- Institute for Theoretical Biology, Department of Biology, Humboldt Universität zu Berlin, Berlin, Germany.,Bernstein Center for Computational Neuroscience, Berlin, Germany
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Pilkiewicz KR, Lemasson BH, Rowland MA, Hein A, Sun J, Berdahl A, Mayo ML, Moehlis J, Porfiri M, Fernández-Juricic E, Garnier S, Bollt EM, Carlson JM, Tarampi MR, Macuga KL, Rossi L, Shen CC. Decoding collective communications using information theory tools. J R Soc Interface 2020; 17:20190563. [PMID: 32183638 PMCID: PMC7115225 DOI: 10.1098/rsif.2019.0563] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 02/28/2020] [Indexed: 02/03/2023] Open
Abstract
Organisms have evolved sensory mechanisms to extract pertinent information from their environment, enabling them to assess their situation and act accordingly. For social organisms travelling in groups, like the fish in a school or the birds in a flock, sharing information can further improve their situational awareness and reaction times. Data on the benefits and costs of social coordination, however, have largely allowed our understanding of why collective behaviours have evolved to outpace our mechanistic knowledge of how they arise. Recent studies have begun to correct this imbalance through fine-scale analyses of group movement data. One approach that has received renewed attention is the use of information theoretic (IT) tools like mutual information, transfer entropy and causation entropy, which can help identify causal interactions in the type of complex, dynamical patterns often on display when organisms act collectively. Yet, there is a communications gap between studies focused on the ecological constraints and solutions of collective action with those demonstrating the promise of IT tools in this arena. We attempt to bridge this divide through a series of ecologically motivated examples designed to illustrate the benefits and challenges of using IT tools to extract deeper insights into the interaction patterns governing group-level dynamics. We summarize some of the approaches taken thus far to circumvent existing challenges in this area and we conclude with an optimistic, yet cautionary perspective.
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Affiliation(s)
- K. R. Pilkiewicz
- Environmental Laboratory, U.S. Army Engineer Research and Development Center (EL-ERDC), Vicksburg, MS, USA
| | | | - M. A. Rowland
- Environmental Laboratory, U.S. Army Engineer Research and Development Center (EL-ERDC), Vicksburg, MS, USA
| | - A. Hein
- National Oceanic and Atmospheric Administration, Santa Cruz, CA, USA
- University of California, Santa Cruz, CA, USA
| | - J. Sun
- Department of Mathematics, Clarkson University, Potsdam, NY, USA
| | - A. Berdahl
- School of Aquatic and Fishery Sciences, University of Washington, Seattle, WA, USA
| | - M. L. Mayo
- Environmental Laboratory, U.S. Army Engineer Research and Development Center (EL-ERDC), Vicksburg, MS, USA
| | - J. Moehlis
- Department of Mechanical Engineering, University of California, Santa Barbara, CA, USA
| | - M. Porfiri
- Department of Mechanical and Aerospace Engineering and Department of Biomedical Engineering, New York University Tandon School of Engineering, Brooklyn, NY, USA
| | | | - S. Garnier
- Department of Biological Sciences, New Jersey Institute of Technology, Newark, NJ, USA
| | - E. M. Bollt
- Department of Mathematics, Clarkson University, Potsdam, NY, USA
| | - J. M. Carlson
- Department of Physics, University of California, Santa Barbara, CA, USA
| | - M. R. Tarampi
- Department of Psychology, University of Hartford, West Hartford, CT, USA
| | - K. L. Macuga
- School of Psychological Science, Oregon State University, Corvallis, OR, USA
| | - L. Rossi
- Department of Mathematical Sciences, University of Delaware, Newark, DE, USA
| | - C.-C. Shen
- Department of Computer and Information Sciences, University of Delaware, Newark, DE, USA
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Behavioural plasticity and the transition to order in jackdaw flocks. Nat Commun 2019; 10:5174. [PMID: 31729384 PMCID: PMC6858344 DOI: 10.1038/s41467-019-13281-4] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2019] [Accepted: 10/25/2019] [Indexed: 12/04/2022] Open
Abstract
Collective behaviour is typically thought to arise from individuals following fixed interaction rules. The possibility that interaction rules may change under different circumstances has thus only rarely been investigated. Here we show that local interactions in flocks of wild jackdaws (Corvus monedula) vary drastically in different contexts, leading to distinct group-level properties. Jackdaws interact with a fixed number of neighbours (topological interactions) when traveling to roosts, but coordinate with neighbours based on spatial distance (metric interactions) during collective anti-predator mobbing events. Consequently, mobbing flocks exhibit a dramatic transition from disordered aggregations to ordered motion as group density increases, unlike transit flocks where order is independent of density. The relationship between group density and group order during this transition agrees well with a generic self-propelled particle model. Our results demonstrate plasticity in local interaction rules and have implications for both natural and artificial collective systems. Modelling collective behaviour in different circumstances remains a challenge because of uncertainty related to interaction rule changes. Here, the authors report plasticity in local interaction rules in flocks of wild jackdaws with implications for both natural and artificial collective systems.
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Ringhofer M, Go CK, Inoue S, S. Mendonça R, Hirata S, Kubo T, Ikeda K, Yamamoto S. Herding mechanisms to maintain the cohesion of a harem group: two interaction phases during herding. J ETHOL 2019. [DOI: 10.1007/s10164-019-00622-5] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/30/2022]
Abstract
AbstractIn animal groups, individual interactions achieve coordinated movements to maintain cohesion. In horse harem groups, herding is a behavior in which males chase females from behind; it is considered to assist with group cohesiveness. However, the mechanisms by which the individuals move to maintain group cohesion are unknown. We applied novel non-invasive methods of drone filming and video tracking to observe horse movements in the field with high temporal and spatial resolution. We tracked all group members and drew trajectories. We analyzed the movements of females and found two phases of interactions based on their timing of movement initiation. The females that moved first were those nearest to the herding male, while the movement initiation of the later females was determined by the distance from the nearest moving female, not by the distance from the herding male. These interactions are unique among animal group movements and might represent a herding mechanism responsible for maintaining group cohesion. This might be due to long-term stable relationships within a harem group and strong social bonds between females. This study showed that the combination of drone filming and video tracking is a useful method for analyzing the movements of animals simultaneously in high resolution.
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Ling H, Mclvor GE, Westley J, van der Vaart K, Yin J, Vaughan RT, Thornton A, Ouellette NT. Collective turns in jackdaw flocks: kinematics and information transfer. J R Soc Interface 2019; 16:20190450. [PMID: 31640502 PMCID: PMC6833319 DOI: 10.1098/rsif.2019.0450] [Citation(s) in RCA: 16] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Accepted: 10/01/2019] [Indexed: 11/12/2022] Open
Abstract
The rapid, cohesive turns of bird flocks are one of the most vivid examples of collective behaviour in nature, and have attracted much research. Three-dimensional imaging techniques now allow us to characterize the kinematics of turning and their group-level consequences in precise detail. We measured the kinematics of flocks of wild jackdaws executing collective turns in two contexts: during transit to roosts and anti-predator mobbing. All flocks reduced their speed during turns, probably because of constraints on individual flight capability. Turn rates increased with the angle of the turn so that the time to complete turns remained constant. We also find that context may alter where turns are initiated in the flocks: for transit flocks in the absence of predators, initiators were located throughout the flocks, but for mobbing flocks with a fixed ground-based predator, they were always located at the front. Moreover, in some transit flocks, initiators were far apart from each other, potentially because of the existence of subgroups and variation in individual interaction ranges. Finally, we find that as the group size increased the information transfer speed initially increased, but rapidly saturated to a constant value. Our results highlight previously unrecognized complexity in turning kinematics and information transfer in social animals.
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Affiliation(s)
- Hangjian Ling
- Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA
- Department of Mechanical Engineering, University of Massachusetts Dartmouth, North Dartmouth, MA, USA
| | - Guillam E. Mclvor
- Centre for Ecology and Conservation, University of Exeter, Penryn, UK
| | - Joseph Westley
- Centre for Ecology and Conservation, University of Exeter, Penryn, UK
| | - Kasper van der Vaart
- Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA
| | - Jennifer Yin
- Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA
| | - Richard T. Vaughan
- School of Computing Science, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Alex Thornton
- Centre for Ecology and Conservation, University of Exeter, Penryn, UK
| | - Nicholas T. Ouellette
- Department of Civil and Environmental Engineering, Stanford University, Stanford, CA, USA
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49
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Inoue S, Yamamoto S, Ringhofer M, Mendonça RS, Hirata S. Lateral position preference in grazing feral horses. Ethology 2019. [DOI: 10.1111/eth.12966] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Affiliation(s)
- Sota Inoue
- Wildlife Research Center Kyoto University Kyoto Japan
| | | | | | - Renata S. Mendonça
- Institute for Advanced Study Kyoto University Kyoto Japan
- Department of Life Sciences Centre for Functional Ecology – Science for People & the Planet University of Coimbra Coimbra Portugal
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50
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Hobson EA, Ferdinand V, Kolchinsky A, Garland J. Rethinking animal social complexity measures with the help of complex systems concepts. Anim Behav 2019. [DOI: 10.1016/j.anbehav.2019.05.016] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/03/2023]
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