Predicting residence time using a continuous-time Markov chain model of satellite telemetry data from Eastern Pacific leatherback turtles

Hoover, AL; Liang, D; Alfaro, J; Dutton, P; Mangel, J; Miller, PI; Morreale, S; Sarti, L; Bailey, H; Shillinger, GL. 2018 Predicting residence time using a continuous-time Markov chain model of satellite telemetry data from Eastern Pacific leatherback turtles. Ecosphere. (In Press)

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Abstract/Summary

The utilization and capabilities of biotelemetry are expanding enormously as technology and access rapidly improve. These large, correlated datasets pose statistical challenges requiring advanced statistical techniques to appropriately interpret and model animal movement. We used satellite telemetry data of critically endangered Eastern Pacific leatherback turtles (Dermochelys coriacea) to develop a habitat-based model of their motility (and conversely residence time) using a hierarchical Bayesian framework, which could be broadly applied across species. To account for the spatiotemporally auto-correlated, unbalanced, and presence-only telemetry observations, in combination with dynamic environmental variables, a novel modeling approach was applied. We expanded a Poisson generalized linear model in a continuous-time discrete-space (CTDS) model framework to predict individual leatherback movement based on environmental drivers, such as sea surface temperature. Population-level movement estimates were then obtained with a Bayesian approach and used to create monthly, near-real time predictions of Eastern Pacific leatherback movement in the South Pacific Ocean. This model framework will inform the development of a dynamic ocean management model, ?South Pacific Turtle Watch (SPTW),? and could be applied to telemetry data from other populations and species to predict motility and resident times in dynamic environments, whilst accounting for statistical uncertainties arising at multiple stages of telemetry analysis.

Item Type: Publication - Article
Additional Information. Not used in RCUK Gateway to Research.: Unmapped bibliographic data: ST - Predicting residence time using a continuous-time Markov chain model of satellite telemetry data from Eastern Pacific leatherback turtles [Field not mapped to EPrints]
Additional Keywords: animal behavior, Bayesian, biologging, CTDS, leatherback turtles, movement, telemetry
Subjects: Conservation
Marine Sciences
Divisions: Plymouth Marine Laboratory > National Capability categories > Added Value
Depositing User: Dr Peter I Miller
Date made live: 04 Jan 2019 14:01
Last Modified: 04 Jan 2019 14:01
URI: http://plymsea.ac.uk/id/eprint/8056

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