| Literature DB >> 34326446 |
Océane Liehrmann1, Jennie A H Crawley2, Martin W Seltmann2, Sherine Feillet2,3, U Kyaw Nyein4, Htoo Htoo Aung4, Win Htut4, Mirkka Lahdenperä5, Léa Lansade6, Virpi Lummaa2.
Abstract
Working animals spend hours each day in close contact with humans and require training to understand commands and fulfil specific tasks. However, factors driving cooperation between humans and animals are still unclear, and novel situations may present challenges that have been little-studied to-date. We investigated factors driving cooperation between humans and animals in a working context through behavioural experiments with 52 working semi-captive Asian elephants. Human-managed Asian elephants constitute approximately a third of the remaining Asian elephants in the world, the majority of which live in their range countries working alongside traditional handlers. We investigated how the familiarity and experience of the handler as well as the elephant's age and sex affected their responses when asked to perform a basic task and to cross a novel surface. The results highlighted that when novelty is involved in a working context, an elephant's relationship length with their handler can affect their cooperation: elephants who had worked with their handler for over a year were more willing to cross the novel surface than those who had a shorter relationship with their handler. Older animals also tended to refuse to walk on the novel surface more but the sex did not affect their responses. Our study contributes much needed knowledge on human-working animal relationships which should be considered when adjusting training methods and working habits.Entities:
Mesh:
Year: 2021 PMID: 34326446 PMCID: PMC8322261 DOI: 10.1038/s41598-021-95048-w
Source DB: PubMed Journal: Sci Rep ISSN: 2045-2322 Impact factor: 4.379
Figure 1Representation of the Myanma Timber Enterprise elephant lifetime and the issues brought by the changing situation in Myanmar leading to numerous mahouts quitting over the last 10 years[17].
Number of successes of elephants at the novel surface task for the different dyads for each crossed category.
| Success/total N | Unknown mahout | Known for less than a year | Known for more than a year |
|---|---|---|---|
| Less experienced | 0/3 | 2/5 | 0/0 |
| Experienced | 0/1 | 2/7 | 2/5 |
| More experienced | 1/3 | 3/8 | 5/9 |
Figure 2Predicted success rate depending on mahout-elephant relationship length. (a—control, b—Novel surface) Bars represent the 95% credibility intervals. (Bayesian regression models from Table 2). “*” means significant differences in between the variables from the extremity of the bracket.
Bayesian regression models analysing elephant success according to their relationship length with the calling mahout (RL: Unknown, < 1 year = Known for less than a year, > 1 year = known for more than a year) and the mahout’s working experience (EXP: Less experienced, Experienced, More experienced). Results from Model 1 are for the control task (N = 51) and results from Model 2 are for the novel surface task (N = 41) Bold = statistically significant variables (CI’s do not encompass 0), italic = tendency effects.
| Explanatory | Estimate ± SE | Lower 95% CI | Upper 95% CI | ||
|---|---|---|---|---|---|
| Control | Model 1 Intercept 1 | ||||
| RL: < 1 year | 0.14 ± 1.67 | − 3.19 | 3.54 | ||
| RL: > 1 year | 0.26 ± 1.76 | − 3.30 | 3.67 | ||
| EXP: Experienced | 1.25 ± 1.83 | − 2.09 | 5.23 | ||
| EXP: More experienced | 1.74 ± 2.00 | − 1.80 | 5.94 | ||
| Model 1 Intercept 2 | |||||
| RL: Unknown | − 0.07 ± 1.72 | − 3.42 | 3.38 | ||
| RL: > 1 year | 0.14 ± 1.51 | − 2.76 | 3.08 | ||
| EXP: Less experienced | − 0.99 ± 1.78 | − 4.77 | 2.39 | ||
| EXP: More experienced | 0.58 ± 1.27 | − 1.87 | 3.07 | ||
| Model 1 Intercept 3 | |||||
| RL: Unknown | − 0.34 ± 1.79 | − 3.71 | 2.61 | ||
| RL: < 1 year | − 0.21 ± 1.47 | − 3.03 | 3.23 | ||
| EXP: Experienced | − 0.57 ± 1.25 | − 3.08 | 2.02 | ||
| EXP: Less experienced | − 1.63 ± 1.97 | − 5.58 | 2.07 | ||
| Novel surface | Model 2 Intercept 1 | ||||
| RL: < 1 year | 7.58 ± 8.59 | − 1.25 | 29.21 | ||
| EXP: Experienced | − 0.85 ± 2.03 | − 5.19 | 2.87 | ||
| EXP: More experienced | 1.06 ± 1.56 | − 1.83 | 4.40 | ||
| Model 2 Intercept 2 | |||||
| RL: Unknown | − 7.40 ± 8.29 | − 29.04 | 1.51 | ||
| RL: > 1 year | 2.54 ± 1.95 | − 0.56 | 6.84 | ||
| EXP: Less experienced | 0.89 ± 2.08 | − 3.34 | 4.91 | ||
| EXP: More experienced | 1.93 ± 1.52 | − 0.68 | 5.27 | ||
| Model 2Intercept 3 | |||||
| RL: < 1 year | − 2.48 ± 2.20 | − 7.28 | 1.05 | ||
| EXP: Experienced | − 1.87 ± 1.53 | − 5.19 | 0.70 | ||
| EXP: Less experienced | − 0.90 ± 1.55 | − 4.31 | 1.89 |
Figure 3Predicted success rate depending on mahout working experience. (a—control, b—Novel surface). Bars represent the 95% credibility intervals. (Bayesian regression models from Table 2).
Figure 4Predicted success rate depending on the task and elephant age (years), (a) control; (b) Novel Surface. Shaded areas show the 95% credibility intervals (Bayesian regression models 3 and 4 from Table 3).
Bayesian regression models analysing elephant success in relation to their age and sex (M = males, F = females) depending on the task (control—Model 3, N = 52; novel surface – Model 4, N = 42). All models included elephant identity nested in the date as random factors. Priors were automatically set by the brms function. Bold = Significant effects (CI’s do not encompass 0), italic = tendency effects.
| Explanatory | Estimate ± SE | Lower 95% CI | Upper 95% CI | |
|---|---|---|---|---|
Control Model 3 | ||||
| Sex: M | 11.87 ± 13.56 | − 4.62 | 41.81 | |
Novel surface Model 4 | ||||
| Elephant age | − 0.68 ± 1.22 | − 3.57 | 0.41 | |
| Sex: M | 2.46 ± 28.35 | − 41.12 | 48.07 |