Efficient Functions for Energetic Least-Cost Analysis over Land and Water in the lbmech package for R

Abstract

Current least-cost tools for behavioral scientists are computationally insufficient and lack methods to independently derive animal-specific energetic cost functions based on locational data. Moreover, topologically-valid approaches only measure the biomechanical cost of movement, when sometimes net metababolical expediture may be a more-important consideration. In this paper, I first derive generalizable cost functions for energetic expenditure for any arbitrary biped or quadruped, versus the currently-employed regressed functions with limited cross-taxa or behavioral mode applicability. I then describe the cost-distance functions of the R package lbmech, designed to (1) regress the parameters describing behavioral sensitivity to slope from GPS tracking data; and (2) calculate the costs of movement in terms of time, kinetic work, and net metabolic expenditure. Finally, I demonstrate the utility of this package using publicly-available GPS, ocean current velocity, and elevation data from the Balearic Islands of Spain. This approach greatly facilitates the collection of field-based data given the reliance on GPS data. Moreover, it allows us to identify and consider individual- and group-level effects and variances that may lead to differential movement-related fitness with evolutionary consequences.