DOI: 10.5061/dryad.368cf90
title: Data from: Movement reveals reproductive tactics in male elephants

description: 1. Long-term bio-logging has the potential to reveal how movements, and
 hence life history trade-offs, vary over a lifetime. Reproductive tactics
 in particular may vary as individuals’ trade-off current investment versus
 lifetime fitness. Male African savannah elephants (Loxodona africana)
 provide a telling example of balancing body growth with reproductive
 fitness due to the combination of indeterminate growth and strongly
 delineated periods of sexual activity (musth), which results in
 reproductive tactics that alter with age. 2. Our study aims to quantify
 the extent to which male elephants alter their movement patterns, and
 hence energetic allocation, in relation to (i) reproductive state and (ii)
 age, and (iii) to determine if musth periods can be detected directly from
 GPS tracking data. 3. We used a combination of GPS tracking data and
 visual observations of 25 male elephants ranging in age from 20-52 years
 to examine the influence of reproductive state and age on movement. We
 then used a three-state hidden Markov model (HMM) to detect musth
 behaviour in a subset of sequential tracking data. 4. Our results
 demonstrate male elephants increase their daily mean speed and range size
 with age and in musth. Furthermore, non-musth speed decreased with age,
 presumably reflecting a shift towards energy acquisition during non-musth.
 Thus, despite similar speeds and marginally larger ranges between states
 at age 20, by age 50 males were travelling 2.0 times faster in 3.5 times
 larger area in musth relative to non-musth. The distinctiveness of musth
 periods over age 35 meant the three-state HMM could automatically detect
 musth movement with high sensitivity and specificity, but could not for
 the younger age class. 5. We show that male elephants increase their
 energetic allocation into reproduction with age as the probability of
 reproductive success increases. Given that older male elephants tend to be
 both the target of legal trophy hunting and illegal poaching, man-made
 interference could drive fundamental changes in elephant reproductive
 tactics. Bio-logging, as our study reveals, has the potential both to
 quantify mature elephant reproductive tactics remotely and to be used to
 institute proactive management strategies around the reproductive
 behaviour of this charismatic keystone species.
description: Transposed GPS tracking
 data underlying the linear mixed effects modelsTransposed elephant GPS
 tracking data underlying the linear mixed effects models. Please note that
 the GPS coordinates have been transposed for each elephant separately and
 are centred on the coordinates of 0,0 to safeguard the elephants by
 anonymising their movement patterns. Requests for the original data can be
 made to Save the Elephants
 (https://www.savetheelephants.org/).Taylor_2019_JAE_RawData_LinearMixedModels.csvTransposed GPS tracking data underlying the three-state hidden Markov modelsTransposed elephant GPS tracking data underlying the three-state hidden Markov models. Please note that the GPS coordinates have been transposed for each elephant separately and are centred on the coordinates of 0,0 to safeguard the elephants by anonymising their movement patterns. Requests for the original data can be made to Save the Elephants (https://www.savetheelephants.org/).Three state HMM data.zipThree-state hidden Markov model codeThree-state hidden Markov model code written in Stan for analysis using the R interface RStan.Taylor_2019_JAE_Three-stateHMM_code.stanExample model output from the three-state hidden Markov modelAn example model output from the three-state hidden Markov model using the elephant 'Matt' as an example.Taylor_2019_JAE_Three-stateHMM_ExampleOutput.txt