Estimation of baboon daily travel distances by means of point sampling – the magnitude of underestimation

Abstract

Abstract. Daily travel distance (DTD), the distance an animal moves over the course of the day, is an important metric in movement ecology. It provides data with which to test hypotheses related to energetics and behaviour, e.g. impact of group size or food distribution on DTDs. The automated tracking of movements by applying GPS technology has become widely available and easy to implement. However, due to battery duration constraints, it is necessary to select a tracking-time resolution, which inevitably introduces an underestimation of the true underlying path distance. Here we give a quantification of this inherent systematic underestimation of DTDs for a terrestrial primate, the Guinea baboon. We show that sampling protocols with interval lengths from 1 to 120 min underestimate DTDs on average by 7 to 35 %. For longer time intervals (i.e. 60, 90, 120 min), the relative increase of deviation from the true trajectory is less pronounced than for shorter intervals. Our study provides first hints on the magnitude of error, which can be applied as a corrective when estimating absolute DTDs in calculations on travelling costs in terrestrial primates.

Estimating day range from camera‐trap data: the animals’ behaviour as a key parameter

“…The problem of underestimating the DR from telemetry data is well known (Rowcliffe et al ., ; Alexander & Maritz, ; Sennhenn‐Reulen et al ., ) and has been demonstrated again in this work. However, the tortuosity correction factor (or the weighted approach based on CT, see below) solved this potential bias.…”

“…The DR has been described as the most costly and time-consuming parameter required for REM application Prichard et al, 2014;Alexander & Maritz, 2015;Sennhenn-Reulen et al, 2017;Nakashima et al, 2018). This signifies that, despite being REM a promising method for implementation in wildlife monitoring programmes, even on large spatial scales (Manzo et al, 2012;Zero et al, 2013;Anile et al, 2014;Cusack et al, 2015;Balestrieri et al, 2016;Rademaker et al, 2016;Caravaggi et al, 2017;Gray, 2018), its application is, at present, considerably limited by the estimation of the DR (Rovero & Marshall, 2009;Alexander & Maritz, 2015;Cusack et al, 2015;Pfeffer et al, 2018).…”

“…The DR has traditionally been estimated with intermittent location data, usually derived from telemetry studies (mainly using GPS devices), and then summing the raw straight-line distances between consecutive locations to attain the total distance (Sennhenn-Reulen et al, 2017;Tucker et al, 2018). However, this approach underestimates the DR because the actual paths between consecutive relocations are not, in fact, straight (Laundre et al, 1987;Reynolds & Laundre, 1990;Rowcliffe et al, 2012;Sennhenn-Reulen et al, 2017); animal paths are mostly tortuous (i.e. characterized by continuous turns).…”

“…This does not, however, solve the problem of tortuosity and other problems emerge, mainly related to fixed accuracy and battery life (Johnson & Ganskopp, 2008;Hurford, 2009;Dewhirst et al, 2016). It is not currently possible to directly record a complete track of tagged individuals with telemetry devices (Dewhirst et al, 2016;Sennhenn-Reulen et al, 2017). Some authors have proposed tracking animals in the snow or the visual tracking of wild animals in parallel with a continuous GPS location series (Musiani, Okarma & Je z drzejewski, 1998;Sennhenn-Reulen et al, 2017), but these approaches are limited to specific areas and individuals that are accustomed to human observers.…”

“…It is not currently possible to directly record a complete track of tagged individuals with telemetry devices (Dewhirst et al, 2016;Sennhenn-Reulen et al, 2017). Some authors have proposed tracking animals in the snow or the visual tracking of wild animals in parallel with a continuous GPS location series (Musiani, Okarma & Je z drzejewski, 1998;Sennhenn-Reulen et al, 2017), but these approaches are limited to specific areas and individuals that are accustomed to human observers. Moreover, this approach is costly and timeconsuming.…”