DOI: 10.5061/dryad.gb5mkkwxt
title: Sex-dependent audience effect in foraging guppies

description: The presence of bystanders can influence the behaviour of a forager, which
 has mainly been studied in primates and birds. We tested the effect of the
 absence and presence of an unfamiliar audience (females, males, and their
 combination) near or far from a food patch, on the foraging behaviour of
 guppies (Poecilia reticulata). Our investigation includes both males and
 females, recognising that different social dynamics and reproductive
 strategies between the sexes could lead to varied responses to audience
 effects. For each focal fish, we measured the latency to start feeding,
 bite frequency, time spent near the audience, and overall mobility. Both
 males and females started feeding faster when food was close to any
 audience type. Specifically, females exhibited a faster feeding response
 in the presence of a female audience. Males reduced their feeding rate in
 the presence of male and mixed audiences, while both sexes increased their
 consumption when food was close to the audience. Focal fish, irrespective
 of their sex, spent more time in the vicinity of the audience zone when
 the audience was present but, surprisingly, females spent less time with a
 female audience compared to others. Only females increased their mobility
 when the food patch was far from any audience. Here we show that guppies
 adjust their foraging behaviour in the presence of an audience. The
 specific responses observed varied between the sexes, reflecting the
 distinct social trade-offs faced by each sex.
description: This dataset was collected through a series of behavioural
 observation trials focusing on the foraging behaviour of guppies,
 differentiated by sex, in the presence and absence of an audience and when
 the food was close or far from the audience. The collection occurred over
 two periods: for female guppies in November 2018, January, and February
 2019, and for male guppies in November 2019, January, and February 2020.
 The methodology was consistent across these periods, involving the
 selection of focal guppies from a stock population, which were then
 isolated in small tanks and deprived of food to standardize hunger levels
 before trials. For the collection process, guppies were selected
 haphazardly 24 hours before their trial, photographed for identification,
 and isolated in individual tanks. The trials were held in experimental
 tanks divided using a transparent barrier that allowed visual and chemical
 communication but segregated focal guppies from an "audience" of
 other four fish selected based on size criteria. The
 processing of this dataset involved several steps:
 <strong>Image Analysis:</strong> Photographs of the
 isolated guppies were analyzed using Image J software to measure their
 standard lengths, providing a quantitative basis for comparisons and
 ensuring that audience fish were appropriately sized in relation to focal
 fish. <strong>Behavioural Recording:
 </strong>During the trials, behaviours were meticulously recorded by
 two observers (NTV, GLN), including latency to start foraging, frequency
 of bites, time spent near the audience, mobility, instances of aggression,
 frequency of courtship displays, and gonopodial swings. This data was
 captured using BORIS software, ensuring systematic and accurate
 recording. <strong>Treatments:</strong> We
 tested 4 audiences: 1) No audience, 2) female audience, 3) male audience,
 and 4) mixed audience. We also tested the proximity of food (close or far)
 from the audience. <strong>Data
 processing:</strong> Initial Data
 Handling: Upon collecting behavioural observations from our experimental
 trials, we meticulously cleaned the raw data to ensure accuracy. This
 involved verifying the correctness of all entries and addressing any
 missing or anomalous data points through established protocols.
 Data Analysis Software: For the analysis of our data, we used R
 (version 4.0.0, R Core Team 2020), which facilitated statistical modelling
 and graphical representation of our results. The 'survival'
 package (Thernau 2020) was used in our analysis of latency to start
 foraging using accelerated failure time regression models.
 Statistical Modelling: Our analysis incorporated a variety of
 statistical methods tailored to the specific nature of each behavioural
 parameter observed. This included: Accelerated
 Failure Time Regression Models: To analyse latency to start foraging,
 allowing us to compare survival curves over time and identify the best fit
 among four common survival distributions (exponential, Weibull,
 log-normal, log-logistic) based on the Akaike information criterion
 (AIC). Generalized Linear Models (GLM): Employed to
 assess the influence of the audience and food patch position on foraging
 behaviour, including frequency of bites and mobility. We addressed
 overdispersion in the frequency of bites and time near the audience using
 the quasi-likelihood method, which is adept at handling variance-mean
 relationships. Model
 Simplification: Following initial model fitting, we engaged in a process
 of backward selection to simplify our models, focusing on the removal of
 non-significant interactions and factors based on probability values and
 AIC for model comparison. This approach enabled us to refine our models to
 those most statistically significant and relevant to our research
 questions. Independent Analysis of Male and Female
 Data: Given the temporal separation of observations for male and female
 guppies, we analysed the data for each sex independently to avoid
 confounding effects and ensure the precision of our findings.
 Exclusion of Certain Behaviours: Due to limited occurrences,
 aggressive and sexual behaviours recorded in focal males were not included
 in the final statistical analysis. This decision was based on the premise
 that the low frequency of these behaviours would not yield statistically
 significant insights. Correlation Analysis: We also
 conducted correlation analyses for key variables (latency to start
 foraging, frequency of bites, time near and far from the audience, and
 mobility) for each sex, with detailed results presented in the
 supplementary data. No Multiple Testing Correction:
 Our approach did not apply a multiple testing correction due to the
 independent analysis of separate datasets for each model. This strategy
 allowed us to thoroughly assess the effects within each specific model
 without the need for cross-model comparison or adjustment for multiple
 comparisons. Compliance with Ethical Standards:
 It's noteworthy to mention that our study adhered strictly to the
 ASAB/ABS Guidelines for the Use of Animals in Research, with all
 procedures approved by BUAP's ethical guidelines.
description: # Sex-dependent audience effect in foraging guppies
 [https://doi.org/10.5061/dryad.gb5mkkwxt](https://doi.org/10.5061/dryad.gb5mkkwxt) ## Description of the data and file structure The data are saved as a CSV file. The dataset is structured in a tabular format with each row representing observational data for a single guppy, identified by a unique ID. Columns within the dataset correspond to specific characteristics and measured behaviors of these guppies during the experimental trials. Here's a breakdown of the structure: * **ID:** Each row corresponds to an individual fish, with its unique identification code (e.g., "1F", "5F"). This ID can be used to track individual fish across different analyses or observational sessions. * **Sex (sex):** Indicates the sex of the focal fish, either female or male. This categorical variable is crucial for analyses that compare behaviours across sexes or that look into sex-specific patterns. * **Size (size):** The standard length (SL) of the fish in centimeters. This quantitative measure is essential for correlating the size of the fish with other behavioural metrics. * **Audience (audience):** The type of audience present during the trial, denoted by abbreviations such as "fe" for female, "co" for control (no audience), "ma" for male, and "mix" for a mixed audience. This variable is key to understanding the social context of the observed behaviors. * **Position (posi):** The position of the food patch, either near or far from the audience. This spatial variable allows researchers to determine the influence of food patch location on foraging behavior. * **Total Frequency of Bites (bites):** The total number of times the fish made oral contact with the food patch over a 20-minute period. This is a central variable for assessing foraging activity. * **Frequency of Bites in First 4 Minutes (bitesfour):** The frequency of bites within the initial four minutes, highlighting the initial response to the food patch. * **Latency to Forage (forlat):** The time taken by the fish to start foraging, in minutes. A lower latency indicates quicker engagement with the food source. * **Mobility (mobi):** The total number of entries and exits from the forage zones, reflecting the fish's activity level within the tank. * **Time Near Audience (timenear):** The duration spent by the focal fish in the zone near the audience, in minutes. This behavioral metric can be used to study social influences on foraging behaviour. * **Time Far from Audience (timefar):** The duration spent in the zone far from the audience, also in minutes. This contrasts with 'timenear' to give a fuller picture of spatial preferences. * **Frequency of Aggressions (agre):** Number of times the focal fish displayed aggressive behaviour towards the audience fish. This variable is important for studies on social dynamics and aggression. * **Courtship (court):** The frequency of courtship displays by focal males, which are indicative of mating behavior and can be influenced by the presence of an audience. * **Gonopodial Swings (gono):** How often the focal male used its gonopodium in a swinging motion, another behavior related to mating. * **Observer (observer):** The person who recorded the data, which is relevant for ensuring consistency in observational data recording. The dataset contains missing values (NaN), particularly in the 'agre', 'court', and 'gono' columns, these behaviours were not observed for females as these behaviors are male-specific.