DOI: 10.5061/dryad.ttdz08m23
title: Adaptive significance of affiliative behaviour differs between sexes in a wild reptile population

description: In recent years, we have begun to appreciate that social behaviours might
 exhibit repeatable among-individual variation. Such behavioural traits may
 even covary and have critical evolutionary implications. Importantly, some
 social behaviours such as aggressiveness have been shown to provide
 fitness benefits, including higher reproductive success and survival.
 However, fitness consequences of affiliative behaviours, especially
 between or among sexes, can be more challenging to establish. Using a
 longitudinal behavioural dataset (2014-2021) collected on eastern water
 dragons (Intellagama lesueurii), we investigated whether various aspects
 of affiliative behaviour (1) were repeatable across years, (2) covaried
 with each other at the among-individual level, and (3) influenced
 individuals’ fitness. In particular, we considered affiliative behaviours
 towards opposite-sex and same-sex conspecifics separately. We found that
 social traits were repeatable and covaried with each other similarly for
 both sexes. More notably, we found that male reproductive success was
 positively correlated with the number of female associates and the
 proportion of time spent with females, whilst females’ reproductive
 success was not correlated with any of the measured social behaviour
 metrics.  Overall, these findings suggest that selection may be
 acting differently on social behaviour of male and female eastern water
 dragons.
description: <strong>Data collection</strong>
 We used data collected as part of an ongoing behavioural study
 that started in 2010 of an urban population of Eastern water dragons
 inhabiting Roma Street Parkland (RSP), Brisbane, Australia (27°27’46’S,
 153°1’11’E). The RSP population has an estimated size of 336 individuals
 which are highly habituated to human presence. The parkland spans
 approximately 16 hectares and is composed of various habitats differing in
 size, complexity and heterogeneity of structure, vegetation and access to
 water. <strong>Behavioural
 data</strong> We carried out behavioural surveys
 twice a day (0730-1030 and 1300-1600), by following a transect which
 covers approximately 85% of the known population, three days a week from
 September to April (when dragons are most active) each year. For each
 individual, we took a photo of their left and/or right profile, along with
 their GPS location which was later used to calculate spatial proximity and
 define social associations (see ‘Social traits’ section). An individual’s
 sex was assigned based on sexual dimorphism and dichromatism. We then
 recorded the individual’s immediate behaviour at the time of the
 observation. Behaviours included a spectrum from resting to agonism (e.g.,
 head bobs, tail slaps, arm waves, chasing, and physical confrontations,
 see for more details). Profile photographs individual
 were used to identify individuals using a previously established method
 for this population. We employed an interactive identification software
 (I3S Spot, v4.0.2), comparing individual facial patterns with an
 established photo library. Those without a match were considered new
 individuals. <strong>Genetic
 data</strong> Animals were caught during sessions
 independent from the behavioural surveys. Each season all possible adult
 individuals were caught using a lassoing technique. A photo was taken of
 each individual for identification upon capture. Blood samples were
 collected using the ventral tail caudal venepuncture technique, while
 tissue samples consisted of collecting the tip of the tail. DNA was
 extracted using DNeasy extraction kits (Qiagen) and sequenced using
 restriction-associated digest methods at Diversity Arrays Technology,
 Canberra, using proprietary DArTcapTM technology. This method applies a
 selective step after complexity reduction to genotype specific markers
 from DArTseq representations, which is a reduced representation sequencing
 approach, similar to RAD-sequencing. Single nucleotide polymorphisms
 (SNPs) were identified using the DArTsoftS pipeline. This resulted in a
 total of 6,425 SNPs prior to filtering, including 510 juveniles (which
 were not included in analyses, but were used in parentage assignment) and
 775 male and female adult individuals.
 <strong>Social traits</strong>
 <em>Social associations</em>
 Social associations were defined as pairs of individuals socially
 tolerating each other in close spatial proximity (1.85m). Details of these
 measurements can be found in the Supplementary methods.
 For each year, the following aspects of social behaviour were
 measured: (1) proportion of time an individual spent within 1.85m of
 conspecifics (i.e., social tendency), (2) number of associates (i.e.,
 degree), and (3) average half-weight association index (hereafter referred
 to as HWI, see supplementary methods for exact calculations). HWI
 estimates the strength of social associations using the weighted
 proportion of time pairs of individuals spend together. Once estimated,
 each social behaviour was divided into two categories: opposite-sex
 associations, and same-sex associations. All social behaviours were
 calculated in individuals’ core home ranges (detailed under ‘Conspecific
 density’ methods), and only individuals with at least 30 sightings per
 year were included, as this represents the minimum number of sightings
 required to estimate stable social measures in this species.
 <em>Conspecific density</em> We
 calculated the density of conspecifics within each individual’s core home
 range (HR50). Core home ranges were estimated using the kernel utilization
 distribution method (UD) in the adehabitatHR package, and a previously
 optimised smoothing parameter of 7m was used to control for the amount of
 variation around density estimates. The coordinates of the 50% probability
 contour were then extracted to obtain HR50. The core home range was chosen
 as this represents individuals’ primary territory and is where most social
 associations occur. Density of conspecifics (hereafter density) was
 estimated for individuals with at least 25 sightings, as this is the
 minimum number required to calculate robust home range estimates. Once
 estimated, density of conspecifics was divided into two categories, namely
 opposite-sex density (i.e., containing overlapping individuals of
 opposite-sex only) and same-sex density (i.e., containing overlapping
 individuals of same-sex only).
 <em>Fitness</em> Fitness was
 defined here as lifetime reproductive success, which was estimated by
 calculating the number of offspring that survived to adulthood (hereafter
 referred to as ‘number of offspring'). To estimate the number of
 offspring, parentage assignments were performed in the sequoia package,
 using SNP data, within the R statistical environment. Sequoia uses a fast,
 heuristic hill-climbing algorithm, which has been shown to result in low
 error and high assignment rates with only a few hundred highly
 informative, unlinked SNPS. SNP data for use in parentage assignment were
 obtained by applying the following filters: (1) read depth of at least 5
 reads per genotype, (2) individual call rate greater than or equal to 70%,
 (3) SNPs call rate greater than or equal to 99%, (4) proportion of
 technical replicate assay pairs for which the marker score was
 consistently greater than or equal to 99%. Minor allele frequency
 threshold (MAF) was chosen by undertaking sensitivity analyses, where we
 generated a set of files in which SNPs were filtered using different MAF
 threshold values (range: 0.38 – 0.47). We then performed parentage
 assignments for each dataset and compared the outputs.
 Parentage assignments obtained from Sequoia were validated in two
 ways. First, we compared them to known maternities resulting from field
 observations of nesting events [40]. Second, genetic relatedness was
 calculated using the maximum-likelihood dyadic relatedness estimator in
 Coancestry. We then plotted parentage assignments against relatedness
 estimates.  SNPs used for the relatedness analysis were obtained from less
 stringent filtering (individual call rate ≥ 80%, SNP call rate ≥ 95%, MAF
 ≥ 0.05, proportion of technical replicate assay pairs ≥ 98%), as a higher
 density of SNPs may increase the accuracy of relatedness estimation. This
 resulted in a total number of 2100 SNPs to estimate relatedness.
 The best MAF value, as indicated by the highest parentage
 assignment and absence of disagreements with field observations was MAF ≥
 0.43, which resulted in a sample size of 179 SNPs used for parentage
 assignment. From the 775 adult individuals included in the parentage
 assignment, 239 dams and 296 sires were assigned surviving adult
 offspring. When validating assignments against known maternities, 98 from
 the 106 were correctly assigned (92%), while 6 mother-offspring pairs were
 not assigned (6%), and 2 were mismatched (2%). These mismatches, however,
 could be the result of mis-assigned mothers from field observations, due
 to nest-sharing events (C.D. pers. observation). While it is possible that
 we may have missed genotyping individuals that would have been assigned to
 other parents, this likelihood is low (overall genetic sampling rate from
 the entire population was 80%).
description: Excel