Movement behavior of a tropical mammal: The case of Tapirus terrestris
Tania Marisol González,
Juan David González-Trujillo,
John R.B. Palmer,
Joan Pino and
Dolors Armenteras
Ecological Modelling, 2017, vol. 360, issue C, 223-229
Abstract:
Animal movement characteristics are not species-specific traits, but rather individual features that respond to various selective pressures. To understand patterns of animal movements, it is especially important to explore how they are affected by differences in landscape and habitat configuration. This paper presents an analysis of the movement patterns of a species of conservation concern in Northwest Amazon, the lowland tapir (Tapirus terrestris), in relation to landscape elements identified as resource concentration areas (palm stands and natural salt licks). We identify the structure of the movement behavior of a sub-adult male lowland tapir using Behavioral Change Point Analysis (BCPA) and a set of metrics capturing velocity and variance. We also estimate this tapir’s Utilization Distribution (UD) using the dynamic Brownian Bridge Movement Model (dBBMM) in order to better understand its trajectories and space-use patterns. Our results provide insights about this animal’s movement, making it possible to differentiate between foraging behaviors, characterized by long trips and selective resource use, and explorative behaviors, characterized by short displacements and a notable decrease in the usage of resource areas and its trajectories. The high influence of landscape elements on movement characteristics suggest that tapirs may perceive the Amazonian forest as heterogeneous rather than homogeneous mosaics. Therefore, the study of movement characteristics proves to be useful for the development of future studies and conservation plans.
Keywords: Animal movement; Relocation data; Telemetry; Spatio-temporal analysis; Brownian models; BCPA (search for similar items in EconPapers)
Date: 2017
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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:360:y:2017:i:c:p:223-229
DOI: 10.1016/j.ecolmodel.2017.07.006
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