 A framework for pre-processing individual location telemetry data for freshwater fish in a river sectionDominique Lamonica, Hilaire Drouineau, Hervé Capra, Hervé Pella and Anthony Maire Ecological Modelling, 2020, vol. 431, issue C Abstract: Animal movement study often relies on individual tracking. The data scale (in time and space) varies according to the species, the environment where individuals live, or the exogenous processes that drive movement. To explore freshwater fish movement in rivers, fine-scale data are needed. Also, in rivers, recorded telemetry frequently shows missing data and location errors. The irregular time-steps, huge amount of data, environmental complexity (river section) and how fish move in such anisotropic environments undermine the use of statistical frameworks such as state-space models. To deal with these specificities, data pre-treatment can be required. We propose a generic method of telemetry data pre-processing, which can be transposed to other datasets. This framework includes interpolation to handle trajectories at fine time scales and performs data analysis within a state-space model. Keywords: Animal location data; Movement model; State-space model; Switching behaviour; Bayesian inference; Parameter estimation (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:431:y:2020:i:c:s0304380020302611 DOI: 10.1016/j.ecolmodel.2020.109190 Access Statistics for this article Ecological Modelling is currently edited by Brian D. Fath More articles in Ecological Modelling from Elsevier |
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