Animal Movement Models

Authored by: Mevin Hooten , Devin Johnson

Handbook of Environmental and Ecological Statistics

Print publication date:  September  2017
Online publication date:  January  2019

Print ISBN: 9781498752022
eBook ISBN: 9781315152509
Adobe ISBN:


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Advancements in biotelemetry technology have led to a rich set of statistical tools for analyzing data arising as observations of spatio-temporal trajectories of individual animals [32]. In this chapter, we focus primarily on biotelemetry (“telemetry” hereafter) data that were recorded as positions in geographical space, denoted as s i , for a set of observation times (termed “fixes”) t 1,…,ti ,…,tn . Methodologically, we review statistical models for satellite derived telemetry data that were collected with fixes close enough together in time that a movement signal is present in the data. The movement signal is a representation of the true path, denoted as μ (t). The characteristics of the true path and its relationship with the environment and other individual paths serves as the primary target for statistical inference in movement ecology. The inherent structure in the individual’s path is often unknown perfectly and presents the primary challenge for statistical modeling. The structure of the path may depend on endogenous correlative properties based on the physics of movement as well as exogenous drivers such as terrain, habitat, and the social structure of populations and communities of animals [6].

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