DOI: 10.5061/dryad.hhmgqnkt2
title: Consistent inter-individual variability in movement traits shapes the wild boar movement syndrome

description: Consistent intraspecific variation in behavior directly impacts reactions
 to environmental challenges, including life in human-altered landscapes.
 Yet, it is rarely considered in free-ranging species thriving in
 anthropogenic landscapes and causing human-wildlife conflict. Here, we
 examine the consistent inter-individual variability in wild boar movement
 traits and highlight its potential for ecology and practical management.
 We used satellite telemetry data from 95 GPS-tracked wild boars monitored
 in Czechia and computed weekly movement rate (activity), intensity of
 space use (exploration), and diurnality (boldness). Using a variance
 partitioning approach, we tested whether these traits were repeatable over
 time and therefore considered personality traits, and using Bayesian
 multivariate mixed-effect models, we examined the correlations among these
 traits to describe a behavioral syndrome while controlling for external
 and internal sources of variation. Wild boar showed significant consistent
 inter-individual variation in all three traits, with repeatability ranging
 from 0.16 to 0.35. We found significant correlations between traits,
 indicating the existence of a remarkable movement syndrome. Individuals
 staying within familiar areas were less nocturnal and moved slower, as
 opposed to individuals roaming more outside familiar areas, faster and
 with striking nocturnality. The movement syndrome and, most importantly,
 its variability, with individuals ranging in between extremes of activity
 and exploration, likely contributes to the success of this species and
 helps them thrive in human-dominated landscapes while maximizing resource
 acquisition. Integrating intraspecific behavioral variation into ecology
 and practical population management could improve models predicting wild
 boar movement and alleviate the biodiversity and economic loss caused by
 expanding wild boar populations.
description: # Consistent inter-individual variability in movement traits shapes the
 wild boar movement syndrome Data for Masilkova et al. "Consistent
 inter-individual variability in movement traits shapes the wild boar
 movement syndrome" (Behavioral Ecology 2025). Dataset
 "wildboar_personality_dataset.csv" (one row = mean weekly values
 of movement traits for individual wild boar, including model covariates)
 contains the following columns: **study_areas** = two study areas (doupov,
 kostelec) **sex** = sex of the wild boar (female, male) **age_class** =
 age class of the wild boar (2 = juvenile, 3 = subadult, 4 = adult)
 **uniqueID** = unique ID of GPS deployment (some individuals were tracked
 with different devices, so each tracking event is identified here)
 **animalID** = ID of individual wild boar **week** = sequential number of
 week in year (from 1 to 53) **mean_p2ptime** = time between fixes; time in
 minutes elapsed between one GPS fix and the next GPS fix
 **mean_forestCover** = forest cover; mean forest cover of all the areas
 traversed by the animal in that week (from 0 = non-forested area to 100 =
 area entirely covered by trees) **mean_hfi** = human footprint index;
 measure of the human pressure (direct and indirect) on the environment for
 the year 2009. Values are means of all the areas traversed by the animal
 in that week. (values from 0 = no human impact to 50 = heavy human impact)
 **mean_distRoads** = distance to roads; distance in meters to
 car/asphalted roads (i.e. classified as "main roads" in the Open
 Street Maps dataset). Values are means of all the areas traversed by the
 animal in that week; computed using osmdata package **mean_distPaths** =
 distance to paths; distance in meters to walkable path restricted to
 offroad vehicles (i.e. classified as "paths" in the Open Street
 Maps dataset). Values are means of all the areas traversed by the animal
 in that week; computed using osmdata package **mean_tri** = terrain
 ruggedness index; Absolute differences between the elevation of a cell and
 its eight surrounding cells, derived from the digital elevation model.
 Values are means of all the areas traversed by the animal in that week;
 computed using terra package **mean_dayLength** = day length; weekly mean
 of the time in hours between sunrise and sunset according to the specific
 location and date; computed using suncalc package **mean_mvmntrate** =
 Euclidean distance (in meters) that the wild boar traveled between
 relocations. Values represent the means of all point to point speeds in a
 week, and are expressed in meters per 30 min. Larger values represent
 faster individuals. **mean_intensity_use** = mean weekly intensity of use
 computed by dividing the total movement distance in a week by the square
 root of the area of the movement of the week (i.e. the minimum convex
 polygon of all locations) with the function intensity_use from the package
 amt (Signer et al. 2019) (lower value = wild boar moving in more
 explorative manner, higher value = wild boar residing in restricted areas)
 **mean_intensity_use_trans** = intensity of use data transformed for
 normality (i.e. log(intensity_of_use + 1) **mean_diurnality** = mean
 weekly diurnality index reflecting an individual´s preference for moving
 during daylight hours while controlling for the lenght of day and night
 computed following Hertel et al. (2019) and using movement rate (values
 from -1 = nocturnal to +1 = diurnal) **mean_diurnality_bin** = mean weekly
 diurnality index transformed into a binary variable by splitting at the
 median value (0 = more nocturnal than the median, 1 = less nocturnal than
 the median)