DOI: 10.5061/dryad.dncjsxm61
title: Data from: A behavioral syndrome of competitiveness in a non-social rodent

description: Animals compete for limited resources and the outcome of intraspecific
 competition should be determined by individual variation in behavioral
 traits, such as aggressiveness, and dominance status. Consistent
 among-individual differences in behavior likely contribute to
 competitiveness and predispose individuals to acquire specific dominance
 ranks. In a step towards better understanding these functional links, we
 studied trait integration into behavioral syndromes, using 26 captive male
 bank voles (Myodes glareolus). We repeatedly assessed boldness in an
 emergence test, exploration in an open-field test, aggressiveness in
 staged dyadic encounters, and the among-individual correlations between
 these behaviors. We further related these personality traits to dominance
 rank, from quantifying urine marking value (UMV), as marking in bank voles
 is related to dominance rank. We found repeatable variations in boldness,
 exploration, aggressiveness, and UMV, which were correlated at the
 among-individual level. Aggressiveness tended to be negatively correlated
 with body condition, a proxy for fitness. Thus, key personality traits and
 social rank are functionally integrated into a behavioral syndrome of
 intraspecific competitiveness.
description: <strong>Study animals</strong>
   We conducted this study on captive
 animals from July-February of 2021 and 2022 in the animal facilities of
 the Animal Ecology Group in Potsdam (Germany). Study animals were male
 bank voles (Myodes glareolus) captured from the wild in a small forest
 patch near Potsdam (Germany)(n = 20) or born in captivity (n = 6) as F1 of
 wild-caught parents. Prior to the experiments, all animals spent 3 to 5
 months in the laboratory and were sexually mature. Voles were housed in
 standard polycarbonate cages (type III and type IV) provided with wood
 shavings and hay as bedding, cardboard rolls as shelter, and a running
 disk for enrichment. Water and food pellets (Ssniff, NM, V 1244-0) were
 available ad libitum.   
 <strong>Personality assessment</strong>
   <em>Emergence test and
 open-field test</em>  
 We tested 26 males twice in two established behavioral tests to
 quantify among-individual differences in activity, exploration, and
 boldness (Mazza et al 2019, Schirmer et al 2019). A circular arena (100 cm
 diameter surrounded by 35 cm high walls) with a white floor connected with
 an opaque tube (11 x 30 cm) with a sliding door was used in both tests. By
 drawing on the floor, the arena was visually divided into a circular
 middle area (70 cm in diameter) where the vole was fully exposed and a
 border area (15 cm wide) by the wall, representing a safer area. Each area
 was additionally visually divided into eight sections.
   We quantified boldness-related
 behaviors via an emergence test, also named dark-light test. The
 individual was placed in the tube for one minute of habituation, after
 which the door to the arena was opened by pulling a string from the
 neighboring room. Based on direct observation (or via video analysis), one
 observer (FE) measured two behavioral variables: the time to emerge with
 the head including ears (latency head) and the latency to emerge with the
 full body excluding the tail (latency body). We quantified activity- and
 exploration-related behaviors via open-field tests. In this test,
 individuals were placed in an inverted beaker at the edge of the arena and
 left to habituate for one minute. Thereafter the beaker was lifted from
 the neighboring room and the individual was observed for 10 minutes. We
 recorded the activity (running, jumping, scanning, grooming)
 instantaneously every 10 seconds, latency to enter the center part of the
 arena with the full body excluding the tail (latency center), number of
 crossings of the full body excluding the tail into the middle part
 (crossings), and the number of different sections entered with its full
 body excluding the tail (sections).  
 <em>Staged dyadic encounters (SDE)</em>
   We ran staged dyadic encounters (SDE)
 between various dyads formed by the 26 male bank voles, to measure
 among-individual variation in behavior towards a conspecific. A total of
 26 took part in three SDE against three different opponents, except for
 one male for which only two encounters (with two different opponents)
 could be performed. To create dyads, we matched individuals of similar
 weight allowing a maximal weight difference of 6 g (corresponding to ≤ 25%
 of the body mass).   SDEs
 were performed in a rectangle box (56.5 x 36.5 x 59.5 cm) divided by a
 wall into two similar-sized compartments (27 x 36.5 x 59.5 cm). The
 dividing wall had a wire grid and a sliding door at the bottom to allow
 visual, acoustic, and olfactory contact between the two compartments after
 the sliding door was pulled up (see Figure SI1 in online resource 1). To
 simplify the video analysis of the placement of voles in the arena, we
 divided the area into three equally big zones (with zone one closest to
 the divider, zone two in the middle, and zone three furthest away from the
 divider) with lines on a paper placed at the bottom of the arena. Animals
 were weighed immediately before testing. We placed dyads in the setup for
 one minute of habituation with the divider down. The arena was then moved
 to the test room for another five minutes of habituation. The observer
 then raised the sliding door from the neighboring room and the voles were
 left to have visual, acoustic, and olfactory contact for 30
 minutes.    One observer
 (FE) quantified movements of the focal vole between the three zones of the
 arena, where movements towards the divider and the opponent vole were
 defined as ‘approaches’ (Figure SI1.A1-A4 in online resource 1) and
 movements away from the divider and the opponent as ‘departures’ (Figure
 SI1.D1-D4 in online resource 1). We quantified, approaches and departures
 by counting crossings of the focal vole between zones with the whole body
 excluding the tail. For each movement between the zones, we additionally
 specified if the vole moved to or from the side of the arena in which the
 opponent vole was located (left or right of the vertical middle), i.e. if
 the vole crossed from one side over the arena, over the midline, to the
 other side of the arena with its full body (excluding the tail). For each
 of these crossings, we also noted down the zone position of the opponent
 vole. Furthermore, we quantified the time spent with its whole body
 (excluding the tail) in the section closest to the divider (‘zone one
 seeker’) and time spent in this section while the opponent also occupies
 zone one in his compartment (‘opponent seeker’). We combined variables
 into fewer variables explaining departures and approaches to opponen,
 including four variables of number of approaches, four variables of number
 of departures, and one variable for all crossings (‘totcross’). The four
 approach variables were: A1) number of all approaches to zone one (closest
 to the divider) disregarding opponent position, A2) number of approaches
 to opponent (to zone one when the opponent is on the same side and
 approaches to the same side as the opponent within zone one), A3) number
 of approaches to zone one only when the opponent also is in zone one, A4)
 number of approaches to opponent (to zone one when the opponent is in the
 same side of zone one and approaches within zone one to the side the
 opponent vole is located in zone one). The four departure variables are
 the opposite movement (i.e. from zone one or opponent) to the
 above-described approach movements (from here on referred to as ‘D1’,
 ‘D2’, ‘D3’, ‘D4’). See figure SI2 in online resource 1 for a visual
 demonstration on how the variables were combined.
   No observer was present in the room of
 the setup during the emergence test, open-field, and SDE. All tests were
 recorded using cameras (ABUS, Mini Dome Camera HDCC35560) and analyzed
 half blinded to the vole identity after tests had been
 conducted.   <em>Urine
 marking value</em>  
 In addition to the SDE described above, we ran a series of
 repeated paired trials to asses urine making behavior of 24 males. Males
 were tested in the same dyads as in the behavioral SDE test. This setup
 consisted of two boxes (27.5 x 40 x 19 cm) attached side by side without a
 floor. The joint walls were perforated with small holes (ca. 0.5 cm
 diameter) to allow olfactory but only limited visual contact between the
 voles in each box. Filter paper was placed under the boxes to capture
 urine markings. We placed dyads in the setup, and left them to interact
 for two hours. Using UV light, we evaluated the filter paper from each
 vole by dividing it into 5 cm x 5 cm squares (35 in total) and counted how
 many of these squares were marked with a few large blots of marking
 (typical for subordinate status) or with many squiggly lines (typical for
 dominant status). An individual only marks typical for subordinate status
 or dominant status. We calculated a urine marking value (UMV) expressed as
 the proportion of the number of squares marked with urine markings of any
 style, subordinate or dominant urine marking patterns, divided by the
 total number of squares. We used the original quantitative variable of the
 proportion of squares marked.  
 After each behavioral test (emergence, open-field, SDE, UMV
 assessment), the animal was transferred back to its home cage, and the
 test arenas were cleaned with ethanol. Each vole was exposed to any of the
 setups only once per day.   
 <em>Body condition</em>
   At the end of the dyadic encounters,
 one observer (FE) measured the head width (mm) of all animals and
 calculated body condition using the scaled body mass index suggested by
 Peig and Green (2009).   
 <em>Statistical analyses</em>
   To analyze among-individual
 correlations between behaviors expressed in the different tests we first
 estimated repeatability of all behavioral variables. Due to it's
 biomodal distribution, we first transformed the time spent in zone one in
 the SDE into a binomial variable using the function “cutoff” from the
 package “cutoff” (Choisy, 2015). We log-transformed all approaches,
 departures, and total crossings from the SDE as well as latency to emerge
 head and body from the emergence test, and arcsine square root transformed
 the proportion spent active in the open-field test and proportion of
 squares with urine marking (UMV). We estimated repeatability using the rpt
 function from the package rptR (Nakagawa and Schielzeth, 2013; Stoffel et
 al., 2017), using 1000 simulations to estimate confidence intervals and
 1000 permutations to estimate p-values. We used Gaussian family
 distribution for variables from the SDE which were
 zero-inflated.   Second, we
 reduced repeatable variables in separate principal component analyses
 (PCA) for each test (emergence, open-field, and SDE) with oblimin rotation
 for the open-field test and SDE. PCA assumptions were checked by
 inspecting the correlation matrix, Bartlett test, and Kaiser-Mayer-Olkin
 (KMO) criterion (Field et al., 2012). We included two variables for the
 PCA of the emergence test, three variables in the PCA for the open-field
 test, and two variables in the PCA of the SDE (Table SI2). If one of these
 behavioral variables had a better distribution than both the principal
 component and the other behavioral variable, we used this original values
 for in the subsequent bivariate mixed models. We only included components
 from the PCA with Eigenvalues &gt; 1 in subsequent bivariate mixed
 models (BMMs).   Third, to
 estimate the fixed effects we ran univariate linear mixed effect models
 using the lmer function from the lme4 package (Bates et al., 2015) or
 generalized mixed effect models using the glmmTMB function from the
 glmmTMB package (Brooks et al., 2017) for each response variable with
 individual identity as a random effect. We evaluated the effect of
 controlling for test occasion (i.e. first, second or third time tested) on
 all response variables, and for body condition on the composite variable
 from the SDE. Due to the large percentage of animals (38%) that did not
 move in the SDE, we additionally ran a GLMM on a binomial variable of
 ‘aggressiveness’, and an LMM on a subset of data with only individuals
 that move as well as controlling for zero-inflation to further assess this
 relationship.   Lastly, to
 investigate among-individual correlations between pairs of variables we
 ran bivariate mixed models (BMMs), using the ‘mcmcglmm’ function from the
 MCMCglmm package (Hadfield, 2010; following procedures described in
 Dingemanse and Dochtermann, 2013 and Houslay and Wilson, 2017). We ran six
 BMMs to evaluate pair-wise correlations between two composite variables
 obtained from the PCAs, crossings, and UMVs. All models included
 individual identity as a random effect and variable-specific fixed effects
 (test occasion for crossings and body condition and test occasion for
 component from SDE). To retain all data in the SDE, we used the
 observations of both individuals in a dyad as independent observation. We
 fixed the within-individual variance to 0 because we did not estimate all
 variables at the same time. We ran all models with different priors as
 suggested by Hadfield 2010 (two informative, two non-informative priors).
 Reported model results are based on a flat uninformative prior (V=diag(2),
 nu=1.002). We used 250,000 iterations, a thinning interval of 100, and a
 burn-in of 50,000. Finally, using the posterior distributions from the
 bivariate mixed models, we calculated repeatability for each dependent
 variable, pairwise among-individual correlations, and their credibility
 intervals based on Houslay and Wilson (2017).
description: # Data from: A behavioral syndrome of competitiveness in a non-social
 rodent
 [https://doi.org/10.5061/dryad.dncjsxm61](https://doi.org/10.5061/dryad.dncjsxm61) ## Description of the data and file structure \# Data from: A behavioral syndrome of competitiveness in a non-social rodent \[Access this dataset on Dryad]([https://doi.org/10.5061/dryad.dncjsxm61](https://doi.org/10.5061/dryad.dncjsxm61)) The dataset contains four excel files of data from behavioral assessment of and one excel file of body metrics of male bank voles. All datasets have a “data” tab for the data and a “labels” tab explaining the data that can be found under the column names in the “data” tab. The individual identification “id” is the same across all files. The file names “emergence”, “open-field”, “SDE”, and “UMV” correspond to the assays explained in detail below. The “body metrics” dataset corresponds to the “body condition” section explained below. The body condition is also present in the SDE dataset. Statistical analysis used to analyze the data is described in the “Statistical analyses” section. This data can be used to evaluate among-individual correlations in behavior. We collected the data for a study on captive animals from July-February of 2021 and 2022 in the animal facilities of the Animal Ecology Group in Potsdam (Germany). Study animals were male bank voles (*Myodes glareolus*) captured from the wild in a small forest patch near Potsdam (Germany)(n = 20) or born in captivity (n = 6) as F1 of wild-caught parents. Prior to the experiments, all animals spent 3 to 5 months in the laboratory and were sexually mature. Voles were housed in standard polycarbonate cages (type III and type IV) provided with wood shavings and hay as bedding, cardboard rolls as shelter, and a running disk for enrichment. Water and food pellets (Ssniff, NM, V 1244-0) were available *ad libitum*.  ### Files and variables #### File: body\_metrics.xlsx **Description:** body metrics data of individuals in assessed for behavior. ##### Variables * *id* = the individual identification of male voles in the behavioral assays, same as the “id” in other data files. * *width* = the head width (mm) * *comment* = comments to the head width measurements, dead indicates that an animal was dead when the measurement was taken (blank cells have no comments) * *closest_bm* = body mass (g) of the temporally closest measurement taken to the head width measurement * *date_bm* = date for when the body mass was taken #### File: UMV.xlsx **Description:** data from paired trials to assess urine marking behavior ##### Variables * *id* = individual identification of the male voles in the experiment, same as the “id” in other data files. * *date* = date at which the test was conducted * *UMV* = the urine marking value scored as the number of squares with urine markings see paper for details (1-35) * *total_squares_visible* = the total number of squares that could be evaluated for UMV * *UMV_factor* = a factor based on the type of markings (D = dominant, S = subordinate) * *test_time* = the temporal length of the test in minutes * *test.occasion* = the orded of the test conducted, (first = 1, second = 2, third = 3 , fourth =4, time tested) * *opponent* = the identification of the opponent * *comments* = any comments to the body condition measurement #### File: README.md **Description:** README for datasets. #### File: SDE.xlsx **Description:** data from staged dyadic encounters for assessing aggressiveness behavior. ##### Variables * *id* = individual identification of the male voles in the experiment, same as the “id” in other data files. * *date* = date at which the test was conducted * *time* = time at which the test was conducted * *test.occasion* = the orded of the test conducted, (first = 1, second = 2, third = 3 , fourth =4, time tested) * t*est_compartment* = which compartment (i.e. which side of the barrier) of the arena the individual was placed * *arena* = which arena out of two identical arenas the animal was placed in * *opponent* = the individual identification (id) of the opponent * *body_mass* = the body mass (g) immediately before the test was conducted * *time_Z1* = time spent in Zone 1 (the zone closest to the barrier and the opponent) * *time_Z1_opponent_Z1* = time spent in Zone 1 (the zone closest to the barrier and the opponent) when the opponent was also in Zone 1 of his compartment of the arena. * *time_Z2* = time spent in zone 2 (the middle zone of the compartment of the arena) * *time_Z3* = time spent in zone 3 (the zone furthest away from the barrier) * *total_time* = total time in test (s) * *A2* = is the number of crossings by the focus individual into Zone 1 (the zone closest to the barrier and the opponent) disregarding the position (which zone or side of the arena) of the opponent (see online resource 1 Figure S2 from Erixon et al. 2024). * *A1* = is the number of crossings into Zone 1 (the zone closest to the barrier and the opponent) when the opponent is on the same side (disregarding zone location) and when the focus individual crosses within Zone 1 to the side in which the opponent is located (disregarding zone location) (see online resource 1 Figure S2 from Erixon et al. 2024) * *A4* = is the number of crossings by the focus individual into Zone 1 (the zone closest to the barrier and the opponent) when the opponent is in Zone 1 but disregarding which side of the arena the opponent is positioned in (see online resource 1 Figure S2 from Erixon et al. 2024). * *A3* = is the number of crossings into Zone 1 (the zone closest to the barrier and the opponent) when the opponent is located in Zone 1 and crossings within Zone 1 to the side the opponent vole is located in (see online resource 1 Figure S2 from Erixon et al. 2024). * *D2* = is the number of crossings by the focus individual out of Zone 1 (the zone closest to the barrier and the opponent) disregarding the position (which zone or side of the arena) of the opponent (see online resource 1 Figure S2 from Erixon et al. 2024). * *D1* = is the number of crossings out of Zone 1 (the zone closest to the barrier and the opponent) when the opponent is on the same side (disregarding zone location) and when the focus individual crosses within Zone 1 away from (D) the side in which the opponent is located (disregarding zone location) (see online resource 1 Figure S2 from Erixon et al. 2024). * *D4* = is the number of crossings by the focus individual out of Zone 1 (the zone closest to the barrier and the opponent) when the opponent is in Zone 1 but disregarding which side of the arena the opponent is positioned in (see online resource 1 Figure S2 from Erixon et al. 2024). * *D3* = is the number of crossings out of Zone 1 (the zone closest to the barrier and the opponent) when the opponent is located in Zone 1 and crossings within Zone 1 away from the side the opponent vole is located in (see online resource 1 Figure S2 from Erixon et al. 2024). * *total_crossings* = total number of crossings between zones in the arena * *comment* = any comments to the test * *body_condition* = the body condition (g) at the start of the test, the index is calculated as the mass (g) of an individual standardized to the mean head width (mm) * *comment_bc* = any comments to the body condition measurement #### File: open\_field.xlsx **Description:** data from open-field test. ##### Variables * *id* = individual identification of the male voles in the experiment, same as the “id” in other data files. * *test.occasion* = the orded of the test conducted, (first = 1, second = 2 , time tested) * *observer* = initials of the observer of the test * *date* = date at which the test was conducted * *time* = time at which the test was conducted * *latency_center* = the latency to enter the center circle with the whole body (excluding the tail) (s) * *crossings* = number of crossings into the center circle with the whole body (excluding the tail) * *sections* = number of sections explored of the arena (1-16) * *activity* = number 10 s interval instances spent active in the arena (1-35) * *inactivity* = number 10 s interval instances spent inactive in the arena (1-35) * *percentage_active* = percentag eof 10 second interval instances spent active (the activity divided by 35 - or less if the activity was impossible to not at any 10 s instance) * *days_between_tests* = the number of days between tests occasions * *comment* = any comments to the test, Na’s and blank cells indicate that there are no comments to the test. #### File: emergence.xlsx **Description:** data from emergence test. ##### Variables * *id* = individual identification of the male voles in the experiment, same as the “id” in other data files. * *test.occasion* = the order of the test conducted, (first = 1, second = 2 , time tested) * *observer* = initials of the observer of the test * *date* = date at which the test was conducted, NA’s indicate when the data does not exist for the animal as the video recording gave up on three occasions. * *time* = time of day at which the test was conducted, NA’s indicate when the data does not exist for the animal as the video recording gave up on three occasions. * *days_between_tests* = the number of days between tests occasions, NA’s indicate are present when data from the second test is missing and there is no record of the number of days between tests. * *latency_head* = the latency to emerge from tube with the whole head (including the ears) (s) , NA’s indicate when the data does not exist for the animal as the video recording gave up on three occasions. * *latency_body* = the latency to emerge from the tube with the whole body (excluding the tail) (s), NA’s indicate when the data does not exist for the animal as the video recording gave up on three occasions. * *comment* = any comments to the test ## Code/Software All analyses were carried out in R, Version 4.3.1.