Dance or disappear: Strategic sexual signalling in female Peninsular rock agama
Data files
Feb 25, 2025 version files 9.57 KB
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behaviour_data_Procb.csv
5.90 KB
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Behaviourdata_mean_CI.csv
347 B
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README.md
3.32 KB
Abstract
Sexual signalling has traditionally been studied in the context of male competition and female mate choice, with female signalling considered of limited consequence. However, there is growing evidence of extensive sexual signalling in females in a wide range of taxa. Here, we test how females strategize the use of sexual signals in a socially polygynous lizard, Psammophilus dorsalis. We evaluated key hypotheses for how females should modulate their signalling, focussing on male quality, mate availability and stage of the breeding season. We simulate male quality using artificial male models to individually tagged, and intensely monitored wild female lizards, measuring their strategic investment in sexual signalling. We found that females invest more in signalling towards high quality males and increased their investment towards the later part of the only breeding season. We demonstrate that, contrary to typical expectations in polygynous systems, females invest in costly sexual signals and adjust their use to maximise benefits and minimise costs. We argue that in spatially dispersed species, females may face limited access to high quality mates, favouring costly sexual signalling. Our findings underscore the need to reassess sexual selection frameworks across taxa, recognising female signalling as an active force in shaping mating dynamics.
https://doi.org/10.5061/dryad.4xgxd25mk
Description of the data and file structure
Files and variables
File: behaviour_data_Procb.csv
Description:
Variables
- lizard.id: Unique ID of lizard
- bead.code: Unique bead code for each lizard (Character that describes the colour of ceramic beads, example WWB mean white,white, blue in the order)
- date: Date (%%dd%%mm%%yyyy)
- model.id: Two colour states were presented - Orange and Yellow (denoted as ORM and YLM)
- prop.redhead: Proportion of time spent in red-head colour state ;Range: 0 to 1 (Time spent in behavioural state/Total observation time)
- prop.crouchposture: Proportion of time spent in crouch posture ;Range: 0 to 1(Time spent in behavioural state/Total observation time)
- prop.tailraise: Proportion of time spent in tail raise posture ;Range: 0 to 1(Time spent in behavioural state/Total observation time)
- prop.darkbody: Proportion of time spent in dark-body colour state ;Range: 0 to 1(Time spent in behavioural state/Total observation time)
- nmal: Number of males in the 20 m vicinity within a 1 month period (This data was obtained from regular surveys. In each survey the number of male neighbours were calculated for every individual female and unique males were calculated for each female)
- breeding: Categories - Early and late breeding season
File: Behaviourdata_mean_CI.csv
Description:
Variables
- Behaviour: The four behaviours - Tail raise, crouch, red-head, dark-body
- Model: Orange and yellow model representing colour states
- mean: Mean
- lower: Lower CI
- upper: Upper CI
Code/software
We used R software.
The workflow begins by loading the necessary libraries, ggplot2 for visualization and glmmTMB for mixed-effects modeling. A cleaned behavioral dataset (behaviour_data_Procb.csv) is then imported, containing pre-filtered behaviors of interest. To estimate variability, a bootstrap function is defined and used to calculate 95% confidence intervals (CI) for prop.tailraise as an example, separately for the YLM and ORM models based on breeding status. Mean values of prop.tailraise as an example are also computed for each model. The same is done for each behaviour and saved in a CSV file (Behaviourdata_mean_CI.csv) and reloaded for visualization. A bar plot is created using ggplot2, displaying mean values with error bars representing CIs, styled for clarity. Since beta regression requires values between 0 and 1, any occurrences of 1 in prop.tailraise are replaced with 0.999. Similar graphs were plotted for other behaviours and conditions. A zero-inflated beta regression model is then fitted to prop.tailraise, incorporating model.id, nmal.cat, and breeding as fixed effects, with lizard.id as a random effect. The same was done for prop.darkbody and prop.redhead. Additionally, since prop.crouchposture is relatively rare, it is converted into a binary presence-absence variable, and a binomial mixed-effects model is fitted.
Access information
Other publicly accessible locations of the data:
- NA
Data was derived from the following sources:
- From data we collected in field
