DOI: 10.5061/dryad.m905qfvft
title: Data from: Spatial strategies in non-territorial societies: How feral horses maintain boundaries with other groups

description: Encounters between competitive individuals or groups are common in social
 animals and can involve costly aggression; thus, animals often employ
 strategies to minimise direct conflict. However, research on whether and
 how animals adjust their group spatial structure when they encounter or
 spatially co-occur with a different group remains limited. We investigated
 how non-territorial units in feral horse multilevel societies manage
 spatial encounters with neighbouring units. We observed 25 reproductive
 units in northern Portugal, using drones, and employed statistical
 analyses to quantify spatial dynamics. We found that horses actively
 adjusted their spatial formations depending on the proximity of other
 units. Units became more circular and cohesive when other units
 approached, but when extremely close, they elongated their shapes to avoid
 boundary crossings. These adjustments indicate that horses maintain
 flexible unit boundaries to prevent mixing with other units. A notable
 exception was a particular pair of units that frequently crossed
 boundaries and intermixed, representing a unique social level within the
 horse multilevel society. Overall, our findings indicate that feral horses
 respond adaptively to inter-unit encounters by balancing the benefits of
 aggregation with the need to reduce direct overlap, providing new insights
 into the spatial organisation of non-territorial societies.　
description: # Data from: Spatial strategies in non-territorial societies: How feral
 horses maintain boundaries with other groups Dataset DOI:
 [10.5061/dryad.m905qfvft](https://doi.org/10.5061/dryad.m905qfvft) ##
 Description of the data and file structure The positional data of feral
 horses was acquired in Serra D'Arga, Portugal, in 2017. We used
 drones to obtain the images of the horses and identified the individuals
 from the aerial photographs. ### Files and variables #### File:
 rawdata_position2017.xlsx **Description:** the positional data of feral
 horses ##### Variables * ID: individual ID - group: group ID * age: age
 class. 'foal' as 0 year old, 'young' as 1-4 years old,
 adult as 5 years old or older. - SEX: sex. 'NA' means sex was
 not identified. * code: the observation code. 60102 represents 6 = June,
 01 = 1st, 02 = 2nd observation of the day. - zone: whether the individual
 was observed at zone 1 or zone 2 in the observation site (see Figure 1 in
 the main manuscript). * xcoord, ycoord: the geographical coordinates of
 the individual. The coordinate system is WGS 84 UTM zone 29N #### File:
 overlap_info.xlsx **Description:** the information of the possible overlap
 events ##### Variables 'overlap' sheet : the code and group ID
 when possible overlap events occurred * uzukobe: "1" = the pair
 is Kobe-Uzumasa, "0" = the pair is not Kobe-Uzumasa - code2: it
 consist of 5 digit to specify the observation time + unit name. For
 example, 60201Asaka means Asaka unit observed at the 1st observation on
 June 2nd. 'radius_nofoal' sheet : the centre and the radius of
 units  * code: same as code2 in the 'overlap' sheet - radius:
 the radius of the unit (m) * xcenter, ycenter: the coordinates of the unit
 center. The coordinate system is WGS 84 UTM zone 29N - code2: the
 observation code. 60102 represents 6 = June, 01 = 1st, 02 = 2nd
 observation of the day. * date: the date of observation. 601 represents 6
 = June, 01 = 1st. - group: unit name #### File: rcode.Rmd
 **Description:** R code for randomisation analysis. This R script runs
 spatial randomization tests to see how often two animal groups’ ranges
 (especially “Uzumasa” and “Kobe”) overlap by chance. It does this by
 shuffling group labels, randomizing positions, or rotating their
 locations, then checking polygon intersections 1000 times. Condition 1:
 Shuffling positions among members of the two units; we randomly shuffled
 the positions of individuals within two units. As males and females tend
 to occupy different positions within a group, the positions of the males
 were fixed, and only the positions of the other members were interchanged.
 In the case of a single-male unit, males were located at the periphery of
 the unit, and in the case of a multiple male unit, subordinate males
 tended to be located at the periphery, with dominant males inside. If the
 observed data under this condition did not significantly deviate from the
 randomised data, this would indicate no intra- or inter-unit
 differentiation in inter-individual distances. Condition 2: Temporal
 permutation without changing unit centres; the internal arrangement of
 individuals in each unit was replaced with that from a different, randomly
 selected observation time when the units were not involved in a possible
 overlap event. The central position of the unit is preserved. This
 condition tested whether horses altered their positions and intra-unit
 distance in response to the proximity or arrangement of other units. If
 the units maintained their positions regardless of the distance from other
 units, the observed data would match the randomised data. Condition 3:
 Rotation around the centre; each unit was rotated around its centre at a
 random angle (0–2π radians) without changing its centre-to-centre distance
 to other units. As inter-individual distances within a unit and distance
 between two-unit centres were preserved, this condition facilitated
 assessment of whether the overall shape, not intra-unit distance, of a
 unit changed depending on its proximity to the other unit. ##
 Code/software MS Excel, R studio used for the analysis ## Access
 information Other publicly accessible locations of the data: * NA Data was
 derived from the following sources: * NA