DOI: 10.5061/dryad.59zw3r2d6
title: Data from: fission-fusion dynamics in sheep: the influence of resource distribution and temporal activity patterns

description: Fission-fusion events, i.e. changes to the size and composition of animal
 social groups, are a mechanism to adjust the social environment in
 response to short-term changes in the cost-benefit ratio of group living.
 Furthermore, the time and location of fission-fusion events provide
 insight into the underlying drivers of these dynamics. Here, we describe a
 method for identifying group membership over time and for extracting
 fission-fusion events from animal tracking data. We applied this method to
 high-resolution GPS data of free-ranging sheep (Ovis aries). Group size
 was highest during times when sheep typically rest (mid-day and at night),
 and when anti-predator benefits of grouping are high while costs of
 competition are low. Consistent with this, fission and fusion frequencies
 were highest during early morning and late evening, suggesting that social
 restructuring occurs during periods of high activity. However, fission and
 fusion events were not more frequent near food patches and water resources
 when adjusted for overall space use. This suggests a limited role of
 resource competition. Our results elucidate the dynamics of grouping in
 response to social and ecological drivers, and we provide a tool for
 investigating these dynamics in other species.
description: The study was conducted at Fowler's Gap Arid Zone Research
 Station in Australia, in 2018. Our study tracked a herd of 50 female
 merino sheep (Ovis aries) interacting in a paddock over 16 days. The
 paddock did not include any other conspecifics, and was approximately 6
 km2 in size. It contained one water trough and 10 food locations
 consisting of bales of hay. The region was severely affected by drought
 and most of the annual vegetation that sheep would graze on was absent.
 Thus, the provided hay constituted the vast majority of food
 resources available to the study animals. We recorded the locations of all
 50 sheep every 6 seconds for 24 hours each day using GPS collars.
 Every four days, sheep were captured to change GPS collar batteries. The
 data from these capture time periods were excluded from the
 analysis. Sheep were undisturbed during the 4-day tracking periods (86 to
 88h each). GPS collars (GPS, i-gotU GT-120 by MobileAction, with a
 larger battery CE04381 by Core Electronics) weighed 700g, approximately
 1.9% of the sheep’s body mass, falling well below the common 5% threshold
 for fitting scientific devices. <br><br>We followed the data
 processing procedure described in Leu et al. (2021) to increase overall
 data quality. Briefly, we first plotted all GPS locations and removed
 obvious outlier locations outside the paddock boundaries. We also removed
 all locations that were determined with fewer than three satellites, which
 is the minimum required for triangulation. Second, we removed locations
 that could not have been reached if the animal moved at maximum speed,
 taking the two previous and two following locations into consideration. We
 used a maximum movement speed of 1.5m/s, which was determined in a
 simulated predation event (Manning et al., 2014). Lastly, because GPS
 units differed slightly in their recording times for each fix, we linearly
 interpolated the data such that each sheep’s location was estimated at
 exactly 6 second intervals. We also filled small gaps in the data using
 the data interpolation (maximum of two consecutive missing locations).
 The processed data comprised 10,362,043 data points, representing 97% of
 the possible maximum number of data points across all sheep and time
 steps.<br><br>Data was further processed with the modified
 DBSCAN algorithm also described in our paper. Groups are built through an
 iterative process, based on DBSCAN. We outline the original DBSCAN before
 adding our modification. The algorithm starts with a randomly picked
 focal sheep and connects all sheep within the given radius to the focal
 sheep and to each other. This approach reflects the “gambit of the
 group”, an assumption that all individuals in a group are associated with
 each other, thus ignoring internal group structure (Franks et al.,
 2010). Then, the algorithm identifies and connects all further individuals
 that are within the radius of any group member. This is repeated until
 no additional sheep can be added to the group. Then, a new focal sheep,
 not yet a member of any group, is chosen, and the iteration starts again.
 The process is repeated until all sheep are assigned to a group or are
 identified as unconnected solitary individuals. The algorithm returns a
 list of the groups for each time step. In its original form, the inputs to
 DBSCAN are 1) a radius that describes the maximum Euclidean distance
 between two individuals considered associated with each other, and 2) an
 integer representing the minimum group size. In our study, we set the
 minimum group size to 1, thus considering groups of any
 size.<br><br>Defining membership in a social group based on a
 spatial radius can result in group membership fluctuating with small
 changes in the distance between individuals, although the social link is
 likely still present. Such fluctuations can be problematic in the context
 of identifying fission-fusion events, because they can lead to the
 detection of many small events that are not biologically/socially
 meaningful. To limit the effect of such fluctuations, we applied a “sticky
 DBSCAN” algorithm, which uses two radii – an inner radius and an outer
 radius. An individual is considered to join another individual in a group
 only if their dyadic distance is smaller than the inner radius. However,
 the time at which the individual joins is identified as the moment when
 the dyadic distance falls below the outer radius. Similarly, an individual
 is considered to leave the group at the time it crosses the outer radius
 of all group members after it has previously been within the inner
 radius.  <br><br>In practice, the “Sticky” DBSCAN algorithm
 starts with a list of the distances of two particular sheep over time. It
 splits at each step where the larger radius r2 is crossed. Now, these time
 spans are dedicated as "connections" or "not
 connections" based on whether they contain at least one distance
 smaller than the small radius r1. The traditional DBSCAN is run now but
 instead of using a radius to determine whether two sheep are connections,
 it uses the Boolean "connection" value. While splitting the
 groups, we ignore any missing data as we will filter out these points in
 the interpolation of group membership step. Since a missing sheep at time
 t will not appear in any of the groups at time t (just as with traditional
 DBSCAN), ignoring them in the "connections" data set only means
 that sheep stay "sticky" associated with their groups during GPS
 outage.<br><br>The sticky DBSCAN algorithm was applied with
 different combinations of radii, which are included in the label. If no
 radii are mentioned in the label, the radii were 30m and
 50m.<br> <br>Franks DW, Ruxton GD, James R. Sampling animal
 association networks with the gambit of the group. Behav Ecol Sociobiol.
 2010 Jan 1;64(3):493–503. Available from: https://doi.org/10.1007/s00265-009-0865-8<br><br>Leu ST, Quiring K, Leggett KEA, Griffith SC. Consistent behavioural responses to heatwaves provide body condition benefits in rangeland sheep. Appl Anim Behav Sci . 2021 Jan 1;234:105204. Available from: https://doi.org/10.1016/j.applanim.2020.105204<br><br>Manning JK, Fogarty ES, Trotter MG, Schneider DA, Thomson PC, Bush RD, et al. A pilot study into the use of global navigation satellite system technology to quantify the behavioural responses of sheep during simulated dog predation events. Anim Prod Sci. 2014 Aug 28; 54(10):1676–81. Available from: https://doi.org/10.1071/AN14221
description: All files have been uploaded as csv files which can be opened by
 a variety of open-source and proprietary resources.
description: # Fission-fusion dynamics in sheep: the influence of resource distribution
 and temporal activity patterns *** The uploaded data contains
 fission-fusion event analysis for several different combinations of radii.
 Whenever not specified, the data uses the radii 30m and 50m as in the
 manuscript's main text. Ts contains the conversion from the time step
 in the first column to Unix time in the second column. The time step is
 the number of data collection points (6s intervals) since the start of
 data collection. PaddockCornersFoodWater contains the coordinates of
 paddock corners, feeding, and water locations, again as coordinates in the
 WGS 84 / UTM zone 54S projection. (A previous version of this file was
 named
 Salt6\_corners\_food\_locations\_collective\_decision\_making\_March2019.csv) GroupsPerTime contains the groups with a row for each time step (see Ts) and each group consists of a list of sheep ID numbers separated by commas. AllCoordinates files contain the centroid/average coordinate of each group using the WGS 84 / UTM zone 54S projection. AllGroupLocationsTimes contains the centroid/average coordinate for each group in the first column (using the WGS 84 / UTM zone 54S projection), the time step at which each group existed in the second column. FissionFusionLocationAndTime files contain the coordinates of identified fission-fusion events (in the WGS 84 / UTM zone 54S projection) in the first column and their time step (see Ts for conversion to Unix time), in the second column. MovementDistances contains the activity level for each sheep at each time step measured as the distance moved in meters since the last measurement. The rows in this file are the sheep ordered by ID numbers (1-51) and the columns are the intervals between time steps also ordered sequentially. HourSquareDistanceEventsNormalisedEventsActivity contains the variables needed for the linear model fit in our publication. The variables are in the order of the file name. Hour is hour of the day, square is an ID for a specific square in the map grid, distance is the nearest resource (food or water), events is the number of fission-fusion events, normalised events is the same number of events divided by the total use of that square, activity is the average distance in meters moved by each sheep in that hour of the day. Squares that were visited for less than 50 time steps in the entire duration of data collection were discarded, which also reduced the number of fission-fusion events from 6831 to 6546. ## Description of the data and file structure Detailed instructions and code for the use of all data have been uploaded with the manuscript to Royal Society Open Science.