Iporangaia – Body condition affecting mating success and parenting behavior
Data files
Oct 18, 2023 version files 65.35 KB
Abstract
Female mate choice is usually based on traits that signal male quality as a sexual partner. According to the ‘good parent hypothesis’, female mate choice may also consider male quality as a caregiver in species with male-only care. Because parental activities may be costly, males in good condition should be more attractive to females than those in poor condition. We experimentally manipulated the body condition of parental and non-parental males of the egg-tending harvestman Iporangaia pustulosa and then evaluated how it affected their mating success and ability to protect eggs under field conditions. For non-parental males, individuals in good condition had twice the probability of mating than those in poor condition. For parental males, individuals in good condition had two times more chances of mating and acquired four times more eggs than those in poor condition. Surprisingly, males’ body condition had no effect on the efficiency of egg protection. Thus, our results indicate that the male condition is a sexually selected trait, but we found no support for the ‘good parent hypothesis’ given that an increase in body condition does not improve the survival of the offspring under male care. Instead, these findings are congruent with predictions of the ‘essential male care’ model, which suggests that, when the costs of parental care are low (as is the case of egg attendance), most males can provide the minimum necessary care for offspring survival. However, only males in good condition can allocate surplus energy to advertise their overall quality and attract more mates.
README: Iporangaia – Body condition affecting mating success and parenting behavior
https://doi.org/10.5061/dryad.3n5tb2rpz
This repository contains all the files used for the statistical analyses of the study "Good body condition increases male attractiveness but not caring quality in a Neotropical arachnid with male-only care". There are several .csv data files, both for Experiment 1 and 2. Additionally, you can find a very detailed RNotebook (.rmd and also in PDF), with all the steps for the analysis, comments, and annotations explaining what was done and the reasoning behind it.
In case of questions, please email Louise Alissa -> ldemorai@ucsc.edu , louisem.alissa@gmail.com
Data Files and their Structures
The data files (.csv) are named with EXP1 and EXP2 and those are referencing if they belong to the analyses of experiment 1 (with non-parental males) or experiment 2 (with parental males). We organized the entire analysis using an RNotebook and, in this notebook, the use of each .csv file is explained and specified.
Important abbreviations, used in a consistent way in all files
We have files for experiments 1 and 2 with information for all inspection visits included in the same dataset; those are EXP1_allvisist.csv and EXP2_allvisists.csv.
In the file EXP1_allvisist.csv we have:
- maleID: identity of males being studied
- exp_group: experimental group; it has two levels GC (good condition) and PC (poor condition)
- visit: the inspection visits done in the field after the body condition manipulation; it has 3 levels, 1, 2 and 3
- sucess_visit: if male received eggs from females, 1; if males did not receive eggs in that time interval between inspection visists, 0
- brood_size: the number of eggs males received in their first episode of egg gain
In the file EXP2_allvisits.csv we have:
- maleID: identity of males being studied
- exp_group: experimental group; it has two levels GC (good condition) and PC (poor condition)
- visit: the inspection visits done in the field after the body condition manipulation; it has 3 levels, 1, 2 and 3
- occasion: the three different times experiment 2 was conducted in order to achieve a reasonable sample size; it has three levels, A, B.C
- days_interval: the number of days between the previous inspection visit in the field and the current visit (that is noted in the same row)
- initial_brood: the number of eggs the males already had when they were initially found
- sucess_visit: if male received eggs from females, 1; if males did not receive eggs in that time interval between inspection visits, 0
- n_egg_gain: the number of eggs gained by males in that inspection visit
- predation_event: if the brood of a given male lost at least one egg due to predation, 1; if males did not lose eggs to predation, 0
- eggs_lost: the number of eggs lot estimated by comparing photos from the previous with the current visit
- eggs_not_lost: older eggs from the previous visit that are still present in the current visit (does not include the eggs that were lost due to predation and also do not include de eggs that hatched)
We also created small files per visit (EXP1_visit1, EXP1_visit2, EXP1_visit3 and EXP2_visit1, EXP2_visit2, EXP2_visit3, all .csv) that follow the same structure as the files with visits merged. The name of some of those columns has the number of the visit added (for example, eggs_lost2) because this made it easier to select the specific variable when writing the codes on R.
Data files used on the tests to verify the manipulation of body condition
Those data files are inputted and used in the last section of our RNotebook, in the Supplementary Information part. They contain the data on the body measurements and weight of males before and after the body condition manipulation.
- ID: identity of males being measured
- exp_group: experimental group; it has two levels GC (good condition) and PC (poor condition)
- DEW: dorsal scute width
- length_before: in mm
- width_before: in mm
- depth_before: in mm
- volume_before: estimate as a elliptical structure mm3, Volume = 4/3 * π * BL/2 * BW/2 * BH/2
- mass_before: to the nearest 0.001 g
- density_before: body mass/body volume g/mm3
- length_after: in mm
- width_after: in mm
- depth_after: in mm
- volume_after: estimate as a elliptical structure mm3, , Volume = 4/3 * π * BL/2 * BW/2 * BH/2
- mass_after: to the nearest 0.001 g
- density_after: body mass/body volume g/mm3
The file manipulation_cohen.csv has the necessary information to calculate the effect size Cohen d for the different times when did the experimental manipulation on males' body condition. The headers are:
- EXP: Which experiment the data is coming from. Experiment 1 manipulation was performed only once, while the Experiment 2 manipulation was conducted 3 times (occasions A, B and C). Occasion A and B follow the exact same protocol, and for this reason, their data is merged; Occasion C had the use of a different equipment.
- exp_group: experimental group; it has two levels GC (good condition) and PC (poor condition)
- manipulation: if the data is from for the beginning (before) or at the end (after) of the body condition manipulation.
- mean: the mean value for males' body density (g/mm3)
- sd: the standard variation in males' body density
Datafiles with the word 'spaghetti' have the data of the experimental manipulation (body density of males before and after the experimental manipulation) organized in a way that was easier to create spaghetti plots (one line for each individual, showing the change in body density before and after the manipulation). We have 3 of those files:
(i) spaghettiEXP1.csv, which includes all males used in experiment 1;
(ii) spaghettiEXP2AB.csv, which includes males that went through the manipulation on occasions A and B;
(iii) spaghettiEXP2Cequip.csv, which includes males that went through the manipulation on occasion C.
The file predation.event.csv is also a small data set used to create a graph, and the data used to create it is explained in the RNotebook. In this file, we have the headers:
- Visit: the inspection visit in the wild that the data is referred; it has 3 levels, visit1, visit2 and visit3
- Exp_group: experimental group; it has two levels GC (good condition) and PC (poor condition)
- total_males_found: the number of males that went through the experimental manipulation and were recaptured in the wild during that visit
- no_predation: from the number of males found, how many had no predation of their eggs
- with_predation: from the males found in that visit, how many had at least one egg lost due to predation
- proportion_with_predation: the proportion of males with predation from the total males found
Code/Software
The analysis was done using R (R version 4.0.2; 2020-06-22) and RStudio (version 1.3.1093).
The code was organized and commented and the results were reported using an RNotebook (a type of RMarkdown file). The list of packages used is listed at the beginning of the RNotebook.
Methods
General description of the experiments
We performed two experiments in which we manipulated the body condition of both non-parental and parental I. pustulosa males, subsequently recording their mating success and number of acquired eggs under natural field conditions. Upon collecting males from the field, we transported them to the laboratory, where they were individually marked with enamel ink. This procedure does not appear to influence the behavior of the individuals (e.g., Requena et al. 2009, 2012; Requena & Machado 2015). Given that harvestmen have very low basal metabolism (Santos 2007), their body condition declines slowly under resting conditions. To accelerate this process, we experimentally forced all males to decline their body condition through a series of physical exercises (i.e., forced walking) in the laboratory. Only after the forced exercise, when we were able to decline the body condition of all males, we assigned them to one of two experimental groups: (a) ‘good condition’ group, in which males received water and food ad libitum, and (b) ‘poor condition’ group, in which males received water ad libitum but no food. We allowed males of the ‘good condition’ group to feed for one day, sufficient to induce significant food intake and, consequently, a marked increase in body condition (Fig. S1 in Supplementary Material). The criteria used to assign males to each of the two experimental groups are presented in Table S1 and Figs. S2-S4.
After the manipulation of body condition, we returned each male to the exact location of capture within our transects. During subsequent visits to the field, a team of four researchers actively surveyed the transects for three consecutive days. They searched for marked males during the afternoon (between 14:00 h and 18:00 h) and the night (between 20:00 h and 00:00 h). During each inspection visit, we recorded whether the recaptured males were successful or unsuccessful in acquiring eggs. To ensure that males were not tending to any clutches, upon encountering a marked male, we carefully searched the vegetation within a 2-meter radius around him. Given that males significantly reduce their movement while caring for eggs (Requena et al. 2012), this searching procedure allowed us to confirm whether a male was unsuccessful in acquiring eggs. For successful individuals, we took photographs of their broods to quantify the number of eggs acquired during the sampling interval, which spanned from one inspection visit to the next.