IDEAS home Printed from https://ideas.repec.org/a/eee/ecomod/v221y2010i17p2008-2017.html
   My bibliography  Save this article

A pioneer validation of a state-space model of vessel trajectories (VMS) with observers’ data

Author

Listed:
  • Walker, E.
  • Bez, N.

Abstract

In the context of the expansion of animal tracking and bio-logging, state-space models have been developed with the objective to characterise animals’ trajectories and to understand the factors controlling their behaviour. In the fisheries community, the electronic tagging of vessels commonly designated by Vessel Monitoring Systems (VMS) is developing and provides a new insight for the understanding, the analysis and the modelling of the trajectories of vessels and their prospecting behaviour. VMS data are thus a clue for the proper definition of fishing effort which remains a fundamental parameter of tuna stock assessments. In this context, we used the VMS (recording of hourly positions) of the French tropical tuna purse-seiners operating in the Indian Ocean to characterise three types of movement (states) on the VMS trajectories (stillness, tracking, and cruising). Based on empirical evidences, and on the regular frequency of VMS acquisition, this was achieved by the development of a Bayesian Hidden Markov model for the speeds and turning angles derived from the hourly steps of the trajectories. In a second phase, states were related to activities disentangling stillness into fishing or stop at sea. Finally the quality of the model performances was rigorously quantified thanks to observers’ data. Confronting model prediction and true activities allowed estimating that 10% of the hourly steps were misclassified. The assumptions and model’ choices are discussed, highlighting the fact that VMS data and observers’ data having different time resolutions, the effective use of validating data was troublesome. However, without validation, these analyses remain speculative. The validation part of this work represents an important step for the operational use of state-space models in ecology in the broad sense (predators’ tracking data, e.g. birds or mammals trajectories).

Suggested Citation

  • Walker, E. & Bez, N., 2010. "A pioneer validation of a state-space model of vessel trajectories (VMS) with observers’ data," Ecological Modelling, Elsevier, vol. 221(17), pages 2008-2017.
  • Handle: RePEc:eee:ecomod:v:221:y:2010:i:17:p:2008-2017
    DOI: 10.1016/j.ecolmodel.2010.05.007
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0304380010002589
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ecolmodel.2010.05.007?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Yann Tremblay & Patrick W Robinson & Daniel P Costa, 2009. "A Parsimonious Approach to Modeling Animal Movement Data," PLOS ONE, Public Library of Science, vol. 4(3), pages 1-11, March.
    2. Vermard, Youen & Rivot, Etienne & Mahévas, Stéphanie & Marchal, Paul & Gascuel, Didier, 2010. "Identifying fishing trip behaviour and estimating fishing effort from VMS data using Bayesian Hidden Markov Models," Ecological Modelling, Elsevier, vol. 221(15), pages 1757-1769.
    3. Gimenez, Olivier & Rossi, Vivien & Choquet, Rémi & Dehais, Camille & Doris, Blaise & Varella, Hubert & Vila, Jean-Pierre & Pradel, Roger, 2007. "State-space modelling of data on marked individuals," Ecological Modelling, Elsevier, vol. 206(3), pages 431-438.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Erico N de Souza & Kristina Boerder & Stan Matwin & Boris Worm, 2016. "Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-20, July.
    2. Guodong Li & Ying Xiong & Xiaming Zhong & Dade Song & Zhongjie Kang & Dongjia Li & Fan Yang & Xiaorui Wu, 2022. "Characterizing Fishing Behaviors and Intensity of Vessels Based on BeiDou VMS Data: A Case Study of TACs Project for Acetes chinensis in the Yellow Sea," Sustainability, MDPI, vol. 14(13), pages 1-16, June.
    3. Floriane Cardiec & Sophie Bertrand & Matthew J Witt & Kristian Metcalfe & Brendan J Godley & Catherine McClellan & Raul Vilela & Richard J Parnell & François le Loc’h, 2020. "“Too Big To Ignore”: A feasibility analysis of detecting fishing events in Gabonese small-scale fisheries," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-19, June.
    4. Woillez, Mathieu & Fablet, Ronan & Ngo, Tran-Thanh & Lalire, Maxime & Lazure, Pascal & de Pontual, Hélène, 2016. "A HMM-based model to geolocate pelagic fish from high-resolution individual temperature and depth histories: European sea bass as a case study," Ecological Modelling, Elsevier, vol. 321(C), pages 10-22.
    5. Tommaso Russo & Lorenzo D'Andrea & Antonio Parisi & Stefano Cataudella, 2014. "VMSbase: An R-Package for VMS and Logbook Data Management and Analysis in Fisheries Ecology," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-18, June.
    6. Boyd, Charlotte & Punt, André E. & Weimerskirch, Henri & Bertrand, Sophie, 2014. "Movement models provide insights into variation in the foraging effort of central place foragers," Ecological Modelling, Elsevier, vol. 286(C), pages 13-25.
    7. Liu, Yuedan & Lee, Sang-Hee & Chon, Tae-Soo, 2011. "Analysis of behavioral changes of zebrafish (Danio rerio) in response to formaldehyde using Self-organizing map and a hidden Markov model," Ecological Modelling, Elsevier, vol. 222(14), pages 2191-2201.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lamonica, Dominique & Drouineau, Hilaire & Capra, Hervé & Pella, Hervé & Maire, Anthony, 2020. "A framework for pre-processing individual location telemetry data for freshwater fish in a river section," Ecological Modelling, Elsevier, vol. 431(C).
    2. Sigourney, Douglas B. & Munch, Stephan B. & Letcher, Benjamin H., 2012. "Combining a Bayesian nonparametric method with a hierarchical framework to estimate individual and temporal variation in growth," Ecological Modelling, Elsevier, vol. 247(C), pages 125-134.
    3. Tong Liu & Angela R Green & Luis F Rodríguez & Brett C Ramirez & Daniel W Shike, 2015. "Effects of Number of Animals Monitored on Representations of Cattle Group Movement Characteristics and Spatial Occupancy," PLOS ONE, Public Library of Science, vol. 10(2), pages 1-17, February.
    4. Russo, Tommaso & Pulcinella, Jacopo & Parisi, Antonio & Martinelli, Michela & Belardinelli, Andrea & Santojanni, Alberto & Cataudella, Stefano & Colella, Sabrina & Anderlini, Luca, 2015. "Modelling the strategy of mid-water trawlers targeting small pelagic fish in the Adriatic Sea and its drivers," Ecological Modelling, Elsevier, vol. 300(C), pages 102-113.
    5. Floriane Cardiec & Sophie Bertrand & Matthew J Witt & Kristian Metcalfe & Brendan J Godley & Catherine McClellan & Raul Vilela & Richard J Parnell & François le Loc’h, 2020. "“Too Big To Ignore”: A feasibility analysis of detecting fishing events in Gabonese small-scale fisheries," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-19, June.
    6. Erico N de Souza & Kristina Boerder & Stan Matwin & Boris Worm, 2016. "Improving Fishing Pattern Detection from Satellite AIS Using Data Mining and Machine Learning," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-20, July.
    7. Woillez, Mathieu & Fablet, Ronan & Ngo, Tran-Thanh & Lalire, Maxime & Lazure, Pascal & de Pontual, Hélène, 2016. "A HMM-based model to geolocate pelagic fish from high-resolution individual temperature and depth histories: European sea bass as a case study," Ecological Modelling, Elsevier, vol. 321(C), pages 10-22.
    8. Aurélie Foveau & Sandrine Vaz & Nicolas Desroy & Vladimir E Kostylev, 2017. "Process-driven and biological characterisation and mapping of seabed habitats sensitive to trawling," PLOS ONE, Public Library of Science, vol. 12(10), pages 1-30, October.
    9. Boyd, Charlotte & Punt, André E. & Weimerskirch, Henri & Bertrand, Sophie, 2014. "Movement models provide insights into variation in the foraging effort of central place foragers," Ecological Modelling, Elsevier, vol. 286(C), pages 13-25.
    10. Paterson, Barbara, 2015. "Tracks, trawls and lines—Knowledge practices of skippers in the Namibian hake fisheries," Marine Policy, Elsevier, vol. 60(C), pages 309-317.
    11. de Ávila-Simas, Sunshine & Morato, Marcelo M. & Reynalte-Tataje, David A. & Silveira, Hector B. & Zaniboni-Filho, Evoy & E. Normey-Rico, Julio, 2019. "Model-based predictive control for the regulation of the golden mussel Limnoperna fortunei (Dunker, 1857)," Ecological Modelling, Elsevier, vol. 406(C), pages 84-97.
    12. Karavarsamis, N. & Huggins, R.M., 2019. "Two-stage approaches to the analysis of occupancy data II. The heterogeneous model and conditional likelihood," Computational Statistics & Data Analysis, Elsevier, vol. 133(C), pages 195-207.
    13. Meritxell Genovart & Roger Pradel, 2019. "Transience effect in capture-recapture studies: The importance of its biological meaning," PLOS ONE, Public Library of Science, vol. 14(9), pages 1-13, September.
    14. Vila, Jean-Pierre, 2012. "Enhanced consistency of the Resampled Convolution Particle Filter," Statistics & Probability Letters, Elsevier, vol. 82(4), pages 786-797.
    15. Choquet, Rémi & Garnier, Alexandre & Awuve, Edem & Besnard, Aurélien, 2017. "Transient state estimation using continuous-time processes applied to opportunistic capture–recapture data," Ecological Modelling, Elsevier, vol. 361(C), pages 157-163.
    16. Bird, Tomas & Lyon, Jarod & Wotherspoon, Simon & King, Ruth & McCarthy, Michael, 2017. "Accounting for false mortality in telemetry tag applications," Ecological Modelling, Elsevier, vol. 355(C), pages 116-125.
    17. Diana J. Cole, 2019. "Parameter redundancy and identifiability in hidden Markov models," METRON, Springer;Sapienza Università di Roma, vol. 77(2), pages 105-118, August.
    18. Pedersen, M.W. & Berg, C.W. & Thygesen, U.H. & Nielsen, A. & Madsen, H., 2011. "Estimation methods for nonlinear state-space models in ecology," Ecological Modelling, Elsevier, vol. 222(8), pages 1394-1400.
    19. Gimenez, Olivier & Mansilla, Lorena & Klaich, M. Javier & Coscarella, Mariano A. & Pedraza, Susana N. & Crespo, Enrique A., 2019. "Inferring animal social networks with imperfect detection," Ecological Modelling, Elsevier, vol. 401(C), pages 69-74.
    20. Demestre, Montserrat & Muntadas, Alba & de Juan, Silvia & Mitilineou, Chryssi & Sartor, Paolo & Mas, Julio & Kavadas, Stefanos & Martín, Javier, 2015. "The need for fine-scale assessment of trawl fishing effort to inform on an ecosystem approach to fisheries: Exploring three data sources in Mediterranean trawling grounds," Marine Policy, Elsevier, vol. 62(C), pages 134-143.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:ecomod:v:221:y:2010:i:17:p:2008-2017. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/ecological-modelling .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.