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Dryad

Agonism does not covary with territoriality in a gregarious reptile dataset

Cite this dataset

Ball, Sarah; Potvin, Dominique; Class, Barbara; Frere, Celine (2023). Agonism does not covary with territoriality in a gregarious reptile dataset [Dataset]. Dryad. https://doi.org/10.5061/dryad.g79cnp5v7

Abstract

Natural selection for territoriality is theorized to occur under conditions favouring intra-sexual phenotypic variation in physiology, morphology and behaviour. In this context, certain suites of behavioural traits associated with territoriality are expected to consistently covary among individuals (sometimes referred to as ‘behavioural syndromes’) within sexes. Agonism (conflict-associated behaviours that may or may not be associated with physical aggression) and movement – for example, ranging, or relocation within or across seasons - are two behavioural components that are associated with territoriality, and may be expected to covary in this context. Territorial males are expected to employ agonistic behaviours to actively establish and defend areas and resources, and show more stability in their location across the landscape. However, the interaction between agonism and movement especially for wild reptiles, has rarely been tested. We investigated whether agonistic and movement behaviour correlate at the individual level both within one year and across multiple years, in a wild population of Australian eastern water dragons, Intellagama lesueurii. Although both types of behaviours exhibited among-individual repeatability over year and multi-year scales, we found no evidence of an agonistic-movement behavioural syndrome. These findings indicate that agonistic and movement behaviours are likely independent traits, and thus territoriality may not drive shared selective pressures for both. It is possible that other social behaviours and strategies are in place to maintain structure in this wild population.

Methods

Behavioural survey data (Agonism)

We utilised data taken as part of a longitudinal study (2010-2020) conducted at Roma Street Parklands, Brisbane, Australia (-27.462315, 153.019052). Between August – May each year, behavioural surveys were recorded three days per week, twice each day (07:30 – 10:30 and 13:00 – 16:00), with the survey route capturing approximately 85% of the water dragon population (Strickland et al. 2014). For every individual encountered, a profile photograph was taken using a Canon EOS 600 digital camera, their GPS coordinates recorded using a GARMIN eTREX10 handheld device, and any agonistic behaviour being exhibited was recorded. Water dragons perform a number of discrete visual and physical behaviours that are considered agonistic or aggressive towards conspecifics. We noted whether, during the survey, the focal individual demonstrated any of the following: head bob, arm wave, tail slap, chasing or fighting. We did not include fighting data for our subsequent analyses, since directionality could not be inferred (i.e. if another individual had begun a fight and the focal individual was acting in defence, rather than demonstrating agonistic behaviour). All other behaviours were pooled, such that an encounter would have recorded an agonistic behaviour, or not (i.e. a binary response variable). Individual ID of each dragon was determined subsequently, thus these observations were done blind to ID.

Individual sex was determined based on known sexual dimorphic characteristics: males present a red ventral colouration which the females lack, and are larger in size than females (Cuervo and Shine 2007). Individuals could then be identified via their photographs in the I3S Manta software using the unique scale patterning around their ear (Gardiner et al. 2014). In addition, once or twice each year a morphological catch took place where we measured individual snout-to-vent length (SVL) from the tip of the snout to the posterior edge of the anal scale, as a measure of body size (Littleford-Colquhoun et al. 2017). All work was done with the approval of the University of the Sunshine Coast Animal Ethics Committee. 

Over the 10-year period we collected 68,452 observations of water dragons with 1,414 unique individuals identified. The data used for these analyses only included adult males that had body size measurements, and therefore consisted of 17,207 observations made for 303 individuals.

Distance measurements (Movement)

We converted GPS points of each individual sighting into x-y coordinates using the adehabitatHR package (Calenge 2006) in the R statistical environment (Team 2010). We then calculated two types of distance measures: successive and displacement. Successive distance was defined as the number of meters between each successive sighting (with time between each) for an individual, and gives an idea of relative location of a territory, and whether the territory centroid shifted directionally over time. Displacement was the number of meters between an individual’s first adult sighting and each subsequent sighting (Fig. 1). Successive distance tends to reveal more about an individual’s daily activity or patrolling (i.e. tendency to always be found in the same place) whereas displacement reflects territory shifts (or the lack of territory) within a season – something that may occur to submissive, younger or transient males. Both traits, however, may be positively correlated with territory size.

In order to determine individual site fidelity between seasons, we calculated the centroid of each home range using the kernel utilisation distribution for each adult male (minimum 20 sightings) at the 95% home range class (Strickland et al. 2017). Following methods from Gardiner et al (2014), we applied a smoothing parameter of seven meters optimised for this species. We then took the centroid coordinates from the projected polygons for each individual per year and measured the distance the centroid had moved between years. This would reveal whether individuals remained in the same area across years or whether they moved their home range site. Site fidelity was then log-transformed, while other movement behaviours were scaled (mean=0; sd=1) in order to improve model convergence.

Funding

Australian Research Council