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Prima MC, Garel M, Marchand P, Redcliffe J, Börger L, Barnier F. Combined effects of landscape fragmentation and sampling frequency of movement data on the assessment of landscape connectivity. MOVEMENT ECOLOGY 2024; 12:63. [PMID: 39252118 PMCID: PMC11385819 DOI: 10.1186/s40462-024-00492-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 07/10/2024] [Indexed: 09/11/2024]
Abstract
BACKGROUND Network theory is largely applied in real-world systems to assess landscape connectivity using empirical or theoretical networks. Empirical networks are usually built from discontinuous individual movement trajectories without knowing the effect of relocation frequency on the assessment of landscape connectivity while theoretical networks generally rely on simple movement rules. We investigated the combined effects of relocation sampling frequency and landscape fragmentation on the assessment of landscape connectivity using simulated trajectories and empirical high-resolution (1 Hz) trajectories of Alpine ibex (Capra ibex). We also quantified the capacity of commonly used theoretical networks to accurately predict landscape connectivity from multiple movement processes. METHODS We simulated forager trajectories from continuous correlated biased random walks in simulated landscapes with three levels of landscape fragmentation. High-resolution ibex trajectories were reconstructed using GPS-enabled multi-sensor biologging data and the dead-reckoning technique. For both simulated and empirical trajectories, we generated spatial networks from regularly resampled trajectories and assessed changes in their topology and information loss depending on the resampling frequency and landscape fragmentation. We finally built commonly used theoretical networks in the same landscapes and compared their predictions to actual connectivity. RESULTS We demonstrated that an accurate assessment of landscape connectivity can be severely hampered (e.g., up to 66% of undetected visited patches and 29% of spurious links) when the relocation frequency is too coarse compared to the temporal dynamics of animal movement. However, the level of landscape fragmentation and underlying movement processes can both mitigate the effect of relocation sampling frequency. We also showed that network topologies emerging from different movement behaviours and a wide range of landscape fragmentation were complex, and that commonly used theoretical networks accurately predicted only 30-50% of landscape connectivity in such environments. CONCLUSIONS Very high-resolution trajectories were generally necessary to accurately identify complex network topologies and avoid the generation of spurious information on landscape connectivity. New technologies providing such high-resolution datasets over long periods should thus grow in the movement ecology sphere. In addition, commonly used theoretical models should be applied with caution to the study of landscape connectivity in real-world systems as they did not perform well as predictive tools.
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Affiliation(s)
- Marie-Caroline Prima
- PatriNat (OFB - MNHN), 75005, Paris, France.
- Office Français de la Biodiversité, Direction de la Recherche et de l'Appui Scientifique, Service Anthropisation et Fonctionnement des Ecosystèmes Terrestres, 38610, Gières, France.
| | - Mathieu Garel
- Office Français de la Biodiversité, Direction de la Recherche et de l'Appui Scientifique, Service Anthropisation et Fonctionnement des Ecosystèmes Terrestres, 38610, Gières, France
| | - Pascal Marchand
- Office Français de la Biodiversité, Direction de la Recherche et de l'Appui Scientifique, Service Anthropisation et Fonctionnement des Ecosystèmes Terrestres, 34990, Juvignac, France
| | - James Redcliffe
- Department of Biosciences, Swansea University, Swansea, SA15HF, UK
| | - Luca Börger
- Department of Biosciences, Swansea University, Swansea, SA15HF, UK
- Centre for Biomathematics, Swansea University, Swansea, SA15HF, UK
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Cantwell-Jones A, Tylianakis JM, Larson K, Gill RJ. Using individual-based trait frequency distributions to forecast plant-pollinator network responses to environmental change. Ecol Lett 2024; 27:e14368. [PMID: 38247047 DOI: 10.1111/ele.14368] [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: 09/18/2023] [Revised: 01/02/2024] [Accepted: 01/04/2024] [Indexed: 01/23/2024]
Abstract
Determining how and why organisms interact is fundamental to understanding ecosystem responses to future environmental change. To assess the impact on plant-pollinator interactions, recent studies have examined how the effects of environmental change on individual interactions accumulate to generate species-level responses. Here, we review recent developments in using plant-pollinator networks of interacting individuals along with their functional traits, where individuals are nested within species nodes. We highlight how these individual-level, trait-based networks connect intraspecific trait variation (as frequency distributions of multiple traits) with dynamic responses within plant-pollinator communities. This approach can better explain interaction plasticity, and changes to interaction probabilities and network structure over spatiotemporal or other environmental gradients. We argue that only through appreciating such trait-based interaction plasticity can we accurately forecast the potential vulnerability of interactions to future environmental change. We follow this with general guidance on how future studies can collect and analyse high-resolution interaction and trait data, with the hope of improving predictions of future plant-pollinator network responses for targeted and effective conservation.
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Affiliation(s)
- Aoife Cantwell-Jones
- Georgina Mace Centre for The Living Planet, Department of Life Sciences, Silwood Park, Imperial College London, Ascot, UK
| | - Jason M Tylianakis
- Georgina Mace Centre for The Living Planet, Department of Life Sciences, Silwood Park, Imperial College London, Ascot, UK
- Bioprotection Aotearoa, School of Biological Sciences, Private Bag 4800, University of Canterbury, Christchurch, New Zealand
| | - Keith Larson
- Climate Impacts Research Centre, Department of Ecology and Environmental Sciences, Umeå University, Umeå, Sweden
| | - Richard J Gill
- Georgina Mace Centre for The Living Planet, Department of Life Sciences, Silwood Park, Imperial College London, Ascot, UK
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Bellisario B, Cardinale M, Maggini I, Fusani L, Carere C. Co-migration fidelity at a stopover site increases over time in African-European migratory landbirds. ROYAL SOCIETY OPEN SCIENCE 2023; 10:221043. [PMID: 37650061 PMCID: PMC10465194 DOI: 10.1098/rsos.221043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 08/11/2023] [Indexed: 09/01/2023]
Abstract
Migratory species are changing their timing of departure from wintering areas and arrival to breeding sites (i.e. migration phenology) in response to climate change to exploit maximum food availability at higher latitudes and improve their fitness. Despite the impact of changing migration phenology at population and community level, the extent to which individual and species-specific response affects associations among co-migrating species has been seldom explored. By applying temporal co-occurrence network models on 15 years of standardized bird ringing data at a spring stopover site, we show that African-European migratory landbirds tend to migrate in well-defined groups of species with high temporal overlap. Such 'co-migration fidelity' significantly increased over the years and was higher in long-distance (trans-Saharan) than in short-distance (North African) migrants. Our findings suggest non-random patterns of associations in co-migrating species, possibly related to the existence of regulatory mechanisms associated with changing climate conditions and different uses of stopover sites, ultimately influencing the global economy of migration of landbirds in the Palearctic-African migration system.
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Affiliation(s)
- Bruno Bellisario
- Department of Ecological and Biological Sciences, University of Tuscia, Viterbo, Italy
| | - Massimiliano Cardinale
- Swedish University of Agricultural Sciences, Department of Aquatic Resources, Institute of Marine Research, Lysekil, Sweden
| | - Ivan Maggini
- Konrad-Lorenz Institute of Ethology, University of Veterinary Medicine, Vienna, Austria
| | - Leonida Fusani
- Konrad-Lorenz Institute of Ethology, University of Veterinary Medicine, Vienna, Austria
- Department of Behavioural and Cognitive Biology, University of Vienna, Vienna, Austria
| | - Claudio Carere
- Department of Ecological and Biological Sciences, University of Tuscia, Viterbo, Italy
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Kraft S, Gandra M, Lennox RJ, Mourier J, Winkler AC, Abecasis D. Residency and space use estimation methods based on passive acoustic telemetry data. MOVEMENT ECOLOGY 2023; 11:12. [PMID: 36859381 PMCID: PMC9976422 DOI: 10.1186/s40462-022-00364-z] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Accepted: 12/26/2022] [Indexed: 06/18/2023]
Abstract
Acoustic telemetry has helped overcome many of the challenges faced when studying the movement ecology of aquatic species, allowing to obtain unprecedented amounts of data. This has made it into one of the most widely used methods nowadays. Many ways to analyse acoustic telemetry data have been made available and deciding on how to analyse the data requires considering the type of research objectives, relevant properties of the data (e.g., resolution, study design, equipment), habits of the study species, researcher experience, among others. To ease this decision process, here we showcase (1) some of the methods used to estimate pseudo-positions and positions from raw acoustic telemetry data, (2) methods to estimate residency and (3) methods to estimate two-dimensional home and occurrence range using geometric or hull-based methods and density-distribution methods, a network-based approach, and three-dimensional methods. We provide examples of some of these were tested using a sample of real data. With this we intend to provide the necessary background for the selection of the method(s) that better fit specific research objectives when using acoustic telemetry.
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Affiliation(s)
- S Kraft
- Center of Marine Sciences (CCMAR), Universidade do Algarve, Faro, Portugal.
| | - M Gandra
- Center of Marine Sciences (CCMAR), Universidade do Algarve, Faro, Portugal
| | - R J Lennox
- Laboratory for Freshwater Ecology and Inland Fisheries at NORCE Norwegian Research Center, Bergen, Norway
- Norwegian Institute for Nature Research (NINA), Trondheim, Norway
| | - J Mourier
- MARBEC, Univ Montpellier, CNRS, Ifremer, IRD, Sète, France
| | - A C Winkler
- Center of Marine Sciences (CCMAR), Universidade do Algarve, Faro, Portugal
- Department of Ichthyology and Fisheries Science, Rhodes University, Makhanda, South Africa
| | - D Abecasis
- Center of Marine Sciences (CCMAR), Universidade do Algarve, Faro, Portugal
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Invasive alien species records are exponentially rising across the Earth. Biol Invasions 2022. [DOI: 10.1007/s10530-022-02843-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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He H, Buchholtz E, Chen F, Vogel S, Yu CA. An agent-based model of elephant crop consumption walks using combinatorial optimization. Ecol Modell 2022. [DOI: 10.1016/j.ecolmodel.2021.109852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
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Morita T, Toyoda A, Aisu S, Kaneko A, Suda-Hashimoto N, Adachi I, Matsuda I, Koda H. Effects of short-term isolation on social animals' behavior: An experimental case study of Japanese macaque. ECOL INFORM 2021. [DOI: 10.1016/j.ecoinf.2021.101435] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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Albery GF, Morris A, Morris S, Pemberton JM, Clutton-Brock TH, Nussey DH, Firth JA. Multiple spatial behaviours govern social network positions in a wild ungulate. Ecol Lett 2021; 24:676-686. [PMID: 33583128 DOI: 10.1111/ele.13684] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2020] [Revised: 12/22/2020] [Accepted: 12/23/2020] [Indexed: 01/19/2023]
Abstract
The structure of wild animal social systems depends on a complex combination of intrinsic and extrinsic drivers. Population structuring and spatial behaviour are key determinants of individuals' observed social behaviour, but quantifying these spatial components alongside multiple other drivers remains difficult due to data scarcity and analytical complexity. We used a 43-year dataset detailing a wild red deer population to investigate how individuals' spatial behaviours drive social network positioning, while simultaneously assessing other potential contributing factors. Using Integrated Nested Laplace Approximation (INLA) multi-matrix animal models, we demonstrate that social network positions are shaped by two-dimensional landscape locations, pairwise space sharing, individual range size, and spatial and temporal variation in population density, alongside smaller but detectable impacts of a selection of individual-level phenotypic traits. These results indicate strong, multifaceted spatiotemporal structuring in this society, emphasising the importance of considering multiple spatial components when investigating the causes and consequences of sociality.
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Affiliation(s)
- Gregory F Albery
- Department of Biology, Georgetown University, Washington, DC, USA.,Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Alison Morris
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Sean Morris
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | | | - Tim H Clutton-Brock
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK.,Department of Zoology, University of Cambridge, Cambridge, UK
| | - Daniel H Nussey
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, UK
| | - Josh A Firth
- Department of Zoology, University of Oxford, Oxford, UK.,Merton College, University of Oxford, Oxford, UK
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Social Network Analysis in Farm Animals: Sensor-Based Approaches. Animals (Basel) 2021; 11:ani11020434. [PMID: 33567488 PMCID: PMC7914829 DOI: 10.3390/ani11020434] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2021] [Revised: 02/01/2021] [Accepted: 02/03/2021] [Indexed: 12/18/2022] Open
Abstract
Simple Summary Social behaviour of farm animals significantly impacts management interventions in the livestock sector and, thereby, animal welfare. Evaluation and monitoring of social networks between farm animals help not only to understand the bonding and agonistic behaviours among individuals but also the interactions between the animals and the animal caretaker. The interrelationship between social and environmental conditions, and the subtle changes in the behaviours of farm animals can be understood and precisely measured only by using sensing technologies. This review aims to highlight the use of sensing technologies in the investigation of social network analysis of farm animals. Abstract Natural social systems within animal groups are an essential aspect of agricultural optimization and livestock management strategy. Assessing elements of animal behaviour under domesticated conditions in comparison to natural behaviours found in wild settings has the potential to address issues of animal welfare effectively, such as focusing on reproduction and production success. This review discusses and evaluates to what extent social network analysis (SNA) can be incorporated with sensor-based data collection methods, and what impact the results may have concerning welfare assessment and future farm management processes. The effectiveness and critical features of automated sensor-based technologies deployed in farms include tools for measuring animal social group interactions and the monitoring and recording of farm animal behaviour using SNA. Comparative analyses between the quality of sensor-collected data and traditional observational methods provide an enhanced understanding of the behavioural dynamics of farm animals. The effectiveness of sensor-based approaches in data collection for farm animal behaviour measurement offers unique opportunities for social network research. Sensor-enabled data in livestock SNA addresses the biological aspects of animal behaviour via remote real-time data collection, and the results both directly and indirectly influence welfare assessments, and farm management processes. Finally, we conclude with potential implications of SNA on modern animal farming for improvement of animal welfare.
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Sosa S, Jacoby DMP, Lihoreau M, Sueur C. Animal social networks: Towards an integrative framework embedding social interactions, space and time. Methods Ecol Evol 2021. [DOI: 10.1111/2041-210x.13539] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Sebastian Sosa
- IPHC UMR 7178 CNRS Université de Strasbourg Strasbourg France
| | | | - Mathieu Lihoreau
- Research Center on Animal Cognition (CRCA) Center for Integrative Biology (CBI) CNRS University Paul Sabatier – Toulouse III Toulouse France
| | - Cédric Sueur
- IPHC UMR 7178 CNRS Université de Strasbourg Strasbourg France
- Institut Universitaire de France Paris France
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