Enhancing the Use of Argos Satellite Data for Home Range and Long Distance Migration Studies of Marine Animals

Xavier Hoenner, Scott Whiting, Mark Hindell, Clive McMahon

    Research output: Contribution to journalArticleResearchpeer-review

    1 Downloads (Pure)

    Abstract

    Accurately quantifying animals' spatial utilisation is critical for conservation, but has long remained an elusive goal due to technological impediments. The Argos telemetry system has been extensively used to remotely track marine animals, however location estimates are characterised by substantial spatial error. State-space models (SSM) constitute a robust statistical approach to refine Argos tracking data by accounting for observation errors and stochasticity in animal movement. Despite their wide use in ecology, few studies have thoroughly quantified the error associated with SSM predicted locations and no research has assessed their validity for describing animal movement behaviour. We compared home ranges and migratory pathways of seven hawksbill sea turtles (Eretmochelys imbricata) estimated from (a) highly accurate Fastloc GPS data and (b) locations computed using common Argos data analytical approaches. Argos 68th percentile error was <1 km for LC 1, 2, and 3 while markedly less accurate (>4 km) for LC ?0. Argos error structure was highly longitudinally skewed and was, for all LC, adequately modelled by a Student's t distribution. Both habitat use and migration routes were best recreated using SSM locations post-processed by re-adding good Argos positions (LC 1, 2 and 3) and filtering terrestrial points (mean distance to migratory tracks � SD = 2.2�2.4 km; mean home range overlap and error ratio = 92.2% and 285.6 respectively). This parsimonious and objective statistical procedure however still markedly overestimated true home range sizes, especially for animals exhibiting restricted movements. Post-processing SSM locations nonetheless constitutes the best analytical technique for remotely sensed Argos tracking data and we therefore recommend using this approach to rework historical Argos datasets for better estimation of animal spatial utilisation for research and evidence-based conservation purposes. � 2012 Hoenner et al.
    Original languageEnglish
    Article numbere40713
    Pages (from-to)1-10
    Number of pages10
    JournalPLoS One
    Volume7
    Issue number7
    DOIs
    Publication statusPublished - 12 Jul 2012

    Fingerprint

    Homing Behavior
    Space Simulation
    remote sensing
    Animals
    Satellites
    Eretmochelys imbricata
    animals
    Conservation
    reworks
    Telemetry
    Animal Behavior
    Turtles
    Ecology
    Research
    sea turtles
    Telemetering
    Ecosystem
    telemetry
    analytical methods
    Observation

    Cite this

    Hoenner, Xavier ; Whiting, Scott ; Hindell, Mark ; McMahon, Clive. / Enhancing the Use of Argos Satellite Data for Home Range and Long Distance Migration Studies of Marine Animals. In: PLoS One. 2012 ; Vol. 7, No. 7. pp. 1-10.
    @article{96dc47a11a1d4fdf82195496106a6e3c,
    title = "Enhancing the Use of Argos Satellite Data for Home Range and Long Distance Migration Studies of Marine Animals",
    abstract = "Accurately quantifying animals' spatial utilisation is critical for conservation, but has long remained an elusive goal due to technological impediments. The Argos telemetry system has been extensively used to remotely track marine animals, however location estimates are characterised by substantial spatial error. State-space models (SSM) constitute a robust statistical approach to refine Argos tracking data by accounting for observation errors and stochasticity in animal movement. Despite their wide use in ecology, few studies have thoroughly quantified the error associated with SSM predicted locations and no research has assessed their validity for describing animal movement behaviour. We compared home ranges and migratory pathways of seven hawksbill sea turtles (Eretmochelys imbricata) estimated from (a) highly accurate Fastloc GPS data and (b) locations computed using common Argos data analytical approaches. Argos 68th percentile error was <1 km for LC 1, 2, and 3 while markedly less accurate (>4 km) for LC ?0. Argos error structure was highly longitudinally skewed and was, for all LC, adequately modelled by a Student's t distribution. Both habitat use and migration routes were best recreated using SSM locations post-processed by re-adding good Argos positions (LC 1, 2 and 3) and filtering terrestrial points (mean distance to migratory tracks � SD = 2.2�2.4 km; mean home range overlap and error ratio = 92.2{\%} and 285.6 respectively). This parsimonious and objective statistical procedure however still markedly overestimated true home range sizes, especially for animals exhibiting restricted movements. Post-processing SSM locations nonetheless constitutes the best analytical technique for remotely sensed Argos tracking data and we therefore recommend using this approach to rework historical Argos datasets for better estimation of animal spatial utilisation for research and evidence-based conservation purposes. � 2012 Hoenner et al.",
    keywords = "accuracy, animal behavior, animal experiment, article, data processing, female, geographic distribution, global positioning system, habitat, home range, marine species, migration, nonhuman, parsimony analysis, prediction, remote sensing, telecommunication, telemetry, turtle, validity, Animal Migration, Animals, Australia, Ecosystem, Female, Geographic Information Systems, Geography, Homing Behavior, Likelihood Functions, Satellite Communications, Turtles, Animalia, Eretmochelys, Eretmochelys imbricata",
    author = "Xavier Hoenner and Scott Whiting and Mark Hindell and Clive McMahon",
    year = "2012",
    month = "7",
    day = "12",
    doi = "10.1371/journal.pone.0040713",
    language = "English",
    volume = "7",
    pages = "1--10",
    journal = "PLoS One",
    issn = "1932-6203",
    publisher = "Public Library of Science (PLoS)",
    number = "7",

    }

    Enhancing the Use of Argos Satellite Data for Home Range and Long Distance Migration Studies of Marine Animals. / Hoenner, Xavier; Whiting, Scott; Hindell, Mark; McMahon, Clive.

    In: PLoS One, Vol. 7, No. 7, e40713, 12.07.2012, p. 1-10.

    Research output: Contribution to journalArticleResearchpeer-review

    TY - JOUR

    T1 - Enhancing the Use of Argos Satellite Data for Home Range and Long Distance Migration Studies of Marine Animals

    AU - Hoenner, Xavier

    AU - Whiting, Scott

    AU - Hindell, Mark

    AU - McMahon, Clive

    PY - 2012/7/12

    Y1 - 2012/7/12

    N2 - Accurately quantifying animals' spatial utilisation is critical for conservation, but has long remained an elusive goal due to technological impediments. The Argos telemetry system has been extensively used to remotely track marine animals, however location estimates are characterised by substantial spatial error. State-space models (SSM) constitute a robust statistical approach to refine Argos tracking data by accounting for observation errors and stochasticity in animal movement. Despite their wide use in ecology, few studies have thoroughly quantified the error associated with SSM predicted locations and no research has assessed their validity for describing animal movement behaviour. We compared home ranges and migratory pathways of seven hawksbill sea turtles (Eretmochelys imbricata) estimated from (a) highly accurate Fastloc GPS data and (b) locations computed using common Argos data analytical approaches. Argos 68th percentile error was <1 km for LC 1, 2, and 3 while markedly less accurate (>4 km) for LC ?0. Argos error structure was highly longitudinally skewed and was, for all LC, adequately modelled by a Student's t distribution. Both habitat use and migration routes were best recreated using SSM locations post-processed by re-adding good Argos positions (LC 1, 2 and 3) and filtering terrestrial points (mean distance to migratory tracks � SD = 2.2�2.4 km; mean home range overlap and error ratio = 92.2% and 285.6 respectively). This parsimonious and objective statistical procedure however still markedly overestimated true home range sizes, especially for animals exhibiting restricted movements. Post-processing SSM locations nonetheless constitutes the best analytical technique for remotely sensed Argos tracking data and we therefore recommend using this approach to rework historical Argos datasets for better estimation of animal spatial utilisation for research and evidence-based conservation purposes. � 2012 Hoenner et al.

    AB - Accurately quantifying animals' spatial utilisation is critical for conservation, but has long remained an elusive goal due to technological impediments. The Argos telemetry system has been extensively used to remotely track marine animals, however location estimates are characterised by substantial spatial error. State-space models (SSM) constitute a robust statistical approach to refine Argos tracking data by accounting for observation errors and stochasticity in animal movement. Despite their wide use in ecology, few studies have thoroughly quantified the error associated with SSM predicted locations and no research has assessed their validity for describing animal movement behaviour. We compared home ranges and migratory pathways of seven hawksbill sea turtles (Eretmochelys imbricata) estimated from (a) highly accurate Fastloc GPS data and (b) locations computed using common Argos data analytical approaches. Argos 68th percentile error was <1 km for LC 1, 2, and 3 while markedly less accurate (>4 km) for LC ?0. Argos error structure was highly longitudinally skewed and was, for all LC, adequately modelled by a Student's t distribution. Both habitat use and migration routes were best recreated using SSM locations post-processed by re-adding good Argos positions (LC 1, 2 and 3) and filtering terrestrial points (mean distance to migratory tracks � SD = 2.2�2.4 km; mean home range overlap and error ratio = 92.2% and 285.6 respectively). This parsimonious and objective statistical procedure however still markedly overestimated true home range sizes, especially for animals exhibiting restricted movements. Post-processing SSM locations nonetheless constitutes the best analytical technique for remotely sensed Argos tracking data and we therefore recommend using this approach to rework historical Argos datasets for better estimation of animal spatial utilisation for research and evidence-based conservation purposes. � 2012 Hoenner et al.

    KW - accuracy

    KW - animal behavior

    KW - animal experiment

    KW - article

    KW - data processing

    KW - female

    KW - geographic distribution

    KW - global positioning system

    KW - habitat

    KW - home range

    KW - marine species

    KW - migration

    KW - nonhuman

    KW - parsimony analysis

    KW - prediction

    KW - remote sensing

    KW - telecommunication

    KW - telemetry

    KW - turtle

    KW - validity

    KW - Animal Migration

    KW - Animals

    KW - Australia

    KW - Ecosystem

    KW - Female

    KW - Geographic Information Systems

    KW - Geography

    KW - Homing Behavior

    KW - Likelihood Functions

    KW - Satellite Communications

    KW - Turtles

    KW - Animalia

    KW - Eretmochelys

    KW - Eretmochelys imbricata

    U2 - 10.1371/journal.pone.0040713

    DO - 10.1371/journal.pone.0040713

    M3 - Article

    VL - 7

    SP - 1

    EP - 10

    JO - PLoS One

    JF - PLoS One

    SN - 1932-6203

    IS - 7

    M1 - e40713

    ER -