Micro-personality traits and their implications for behavioural and movement ecology research
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https://datadryad.org/dataset/doi:10.5061/dryad.tmpg4f4xp
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Many animal personality traits have implicit movement‐based definitions,
and can directly or indirectly influence ecological and evolutionary
processes. It has therefore been proposed that animal movement studies
could benefit from acknowledging and studying consistent inter-individual
differences (personality), and, conversely, animal personality studies
could adopt a more quantitative representation of movement patterns. Using
high-resolution tracking data of three-spined stickleback fish
(Gasterosteus aculeatus), we examined the repeatability of four movement
parameters commonly used in the analysis of discrete time-series movement
data (time stationary, step-length, turning angle, burst frequency), and
four behavioural parameters commonly used in animal personality studies
(distance travelled, space use, time in free water, time near objects).
Fish showed repeatable inter-individual differences in both movement and
behavioural parameters when observed in a simple environment with two,
three, or five shelters present. Moreover, individuals that spend less
time stationary, take more direct paths and less commonly burst travel
(movement parameters), were found to travel farther, explored more of the
tank, and spent more time in open water (behavioural parameters). Our
case-study indicates that the two approaches – quantifying movement and
behavioural parameters – are broadly equivalent, and we suggest that
movement parameters can be viewed as “micro-personality” traits that give
rise to broad-scale consistent inter-individual differences in behaviour.
This finding has implications for both personality and movement ecology
research areas. For example, the study of movement parameters may provide
a robust way to analyse individual personalities in species that are
difficult or impossible to study using standardised behavioural assays.
提供机构:
Dryad
创建时间:
2021-01-25



