DOI: 10.5061/dryad.pvmcvdntb
title: Data from: The evolution of sex roles: The importance of ecology and social environment

description: Males and females often have different roles in reproduction, although the
 origin of these differences have remained controversial. Explaining the
 enigmatic reversed sex roles where males sacrifice their mating potential
 and provide full parental care is a particularly long-standing challenge
 in evolutionary biology. While most studies focused on ecological factors
 as the drivers of sex roles, recent research highlights the significance
 of social factors such as the adult sex ratio. To disentangle these
 propositions, here we investigate the additive and interactive effects of
 several ecological and social factors on sex role variation using
 shorebirds (sandpipers, plovers and allies) as model organisms that
 provide the full spectrum of sex role variation including some of the best
 known examples of sex role reversal. Our results consistently show that
 social factors play a prominent role in driving sex roles. Importantly, we
 show for the first time that reversed sex roles are associated with both
 male-skewed adult sex ratios and high breeding densities. Furthermore,
 phylogenetic path analyses provide the first general support for sex
 ratios driving sex role variations rather than being a consequence of sex
 roles. Together, these novel results open a new research direction by
 showing that different mating opportunities of males and females play a
 major role in generating the evolutionary diversity of sex roles, mating
 system and parental care.
description: All data were collected from published literature or open
 databases. We extensively searched the primary literature reporting the
 behavioral, demographic, and ecological variables used in this study
 through Web of Knowledge and Google Scholar. We used the keywords
 ‘shorebird’, ‘wader’, or the English and Latin name of species in
 combination with ‘sex ratio’, ‘sex role’, ‘mating system’, ‘polygamy’,
 ‘parental care’, ‘breeding’, or ‘population monitoring’. We also attempted
 to locate and screen-specific publication on shorebirds not available
 through the above databases (e.g., annual population reports, taxon
 specialists' group reports). First, because ASR was usually the
 limiting information, we searched for data on this variable to update and
 extend the dataset used in Liker <em>et al</em>. Nature
 (2013). Then, for the species with ASR estimates, we also screened the
 sources for other variables (mating system, parental care, hatching
 success, breeding density, see below). Data collection was conducted
 between January 2019 and June 2020. The total number of records and
 populations and their references are given in Supplementary Table S5 of
 the paper.
description: # Data from: The evolution of sex roles: The importance of ecology and
 social environment
 [https://doi.org/10.5061/dryad.pvmcvdntb](https://doi.org/10.5061/dryad.pvmcvdntb) ## Description of the data and file structure **DataSpeciesLevel:** Species: Species latin name Phylo: Species latin name for the phylogenetic tree (some changed since) Latitude: Latitude (Average of the latitude of the population used for NDVI) NHatching_success: Number of population used for Hatching success NASR: Number of population used for ASR (Adult Sex Ratio) NDensity: Number of population used for Density NNDVI: Number of population used for NDVI (Normalized difference vegetation index) ParentalCareBias: Parental care bias species specific ParentalCareDurationBias: Parental care Duration bias species specific PolygamyFrequencyBias: polygamy frequency bias species specific - NA means that no data were found in the literature for this species PolygamyScoreBias: polygamy score bias species specific - NA means that no data were found in the literature for this species Hatching_successRaw: Hatching success population average ASRRaw: ASR(Adult Sex Ratio) population average DensityRaw: Breeding Density population average Hatching_successEstimate: Hatching success Estimate ASREstimate: ASR (Adult Sex Ratio) Estimate DensityEstimate: Breeding Density Estimate NDVILog: NDVI (Normalized difference vegetation index) log transformed **DataDetails:** For each variable: Adult sex ratio, Breeding density and Hatching success, intraclass correlation (ICC) is given to measure the repeatability between population. See after for more details on the variables. Species: Species latin name NRecords: Total number of records obtained for this species (line) and this variable (column). Several records can come from the same population and/or the same study (e.g. yearly estimates) NPopulations: We considered as a population a specific location (given by precise coordinates). Several studies can use the same population Quality: See methods for the scoring of quality, number within bracket give the number of records with this quality score, if no number are given then all records have the same quality References: References of papers where the data were extracted (see References sheet) **Please read the methods in the Paper for more details.** Polygamy frequency bias: difference between the estimated percentages of the male’s and female’s polygamy. For each species, we recorded the percentage of individuals in a population that breed in social polygamy, separately for males (i.e., polygyny) and females (i.e., polyandry). We recorded any type of social polygamy (sequential or simultaneous) if it was observed within the same breeding season. Lekking birds (in our dataset: pectoral sandpiper, buff-breasted sandpiper *Calidris subruficollis*, ruff, American woodcock and Eurasian woodcock *Scolopax rusticola*) do not exhibit social pair bonds, thus, to express the common assumption that male–male competition is intense in lekking species, we allocated 100% male polygamy for these species. We used the logit transformation for this variable before analyses. Polygamy score bias: difference between male polygamy score and female polygamy score. We scored evidence of polygamy for males and females separately on a scale of 0–4, with 0 corresponding to no (or very rare) polygamy (&lt; 0.1% of individuals when quantitative data are available), 1 to rare polygamy (0.1–1%), 2 to uncommon polygamy (1–5%), 3 to moderate polygamy (5–20%) and 4 to common polygamy (&gt; 20%). The scoring of polygamy frequency is highly and significantly repeatable between two independent observers (intraclass correlation, ICC = 0.914, 22). Parental care score bias: total male participation in parental care relative to females. Scores were calculated on a scale of 0 to 4 for five forms of parental activities: nest building, incubation, nest guarding, chick brooding and chick guarding. For each form of care, score 0 indicated no male participation (i.e. all care carried out by females), score 1 indicated substantially more female than male care (1–33% male care when quantitative data were available), score 2 indicated similar role of the sexes (34–66% male care), score 3 indicated substantially more male than female care (67–99% male care), and score 4 indicated 100% male care (i.e. no female care). These scores were based on quantitative data if available (e.g., % incubation provided by males) or on qualitative descriptions of care in the data sources. We calculated the average of the scores of the five investigated parental activities, with higher scores meaning more care provided by the males. The scoring is highly and significantly repeatable between observers (ICC = 0.792, 22). Parental care duration bias: sex bias in parental care duration. We divided the total length of parental care into 7 periods: 1-3 for incubation, 4-7 for brood care. If one sex deserts the brood before incubation it was given a score of 0, if one sex cares until the chicks fledge it was given a score of 7, and intermediate scores represent desertion between these extremes and are proportional with time the parents are present during incubation and brood care. Then sex bias was calculated as the difference between male and female scores. NDVI (Habitat productivity): NDVI (Normalized difference vegetation index) data were obtained from Moderate Resolution Imaging Spectroradiometer (MODIS, NASA EOSDIS Land Processes DAAC) using Google Earth engine to access the “MOD13A2” data (109). NDVI was calculated from a sample of 1km2 resolution for all populations in our dataset using geographic information given in the studies (i.e., geographic coordinates or name of the study place). For each population, we extracted all available NDVI values from the years 2000-2010 during the breeding season of the targeted species. Then we calculated the median values (to avoid biases due to extreme values) in order to have only one data point per population. When we had data from several populations for a species, we used the average NDVI values of the populations in the final species-level analyses (see below). MODIS-NDVI data are not available before 2000 so we chose the oldest available data from this database, and we used 10 years of data to avoid biased results due to years with unusual conditions (which were likely more frequent in more recent years). We log-transformed the final NDVI estimate obtained per species, and then squared and zero-centered to obtain a distribution in the same range as in other variables (see “Species estimates from raw data” hereafter). Hatching success: Hatching success was estimated as the percentage of nests in a population that hatched at least one egg. We scored the quality of data as either low when the study included only a small subset of nests from the population, or only from a part of the breeding season, or if the methodology is not well detailed (31 records out of 191); or good when the study represented more than half of the total nests of the population and measured throughout the breeding season (160 records out of 191). Adult sex ratio (ASR): We calculated adult sex ratio as the proportion of males in the adult population (107, 110). We also recorded the sample size (number of individuals) and the time of sampling (breeding season: 96 records; non-breeding season: 41 records; all year: 12 records; or during an unknown period: 8 records out of 157) for all ASR estimates. We also gave a quality score for each record on a 0-3 scale: 0 when the quality could not be estimated (6 records out of 157), 1 being a low quality record (i.e. only a small fraction of the local population censused, and/or the method may be biased, 48 records out of 157), 2 being a medium quality (i.e. a significant part of the population was counted/captured, and the method was likely unbiased, 45 records out of 157) and 3 being a good quality (i.e. all or most individuals of the local population were counted or captured or a significant part of the population was counted or captured, with an effort to make the method unbiased; or the ASR was obtained from statistical models based on good quality data, 58 records out of 157). For 20 of the 41 species we obtained data for more than one population, and for 25 populations (21 species) ASR was separately estimated for multiple years (resulting in the total of 157 records). Breeding density: The raw data of breeding density was extracted as individuals or pairs per km². We considered any type of breeding density estimate due to differences in the survey methods and data availability between species. We recorded the method of the studies according to which type of breeding density was estimated (i.e., nest, pair, breeder, or total population counts). In order to re-adjust the density obtained by different methods to an approximately similar scale, we divided ‘breeder density’ and ‘population density’ by two thus we used breeding density as pair/km² in our statistical models. We also recorded data quality as either low quality record (if density was calculated only on a small portion of the population or if the methods were not detailed, 42 records out of 339) or good quality record (i.e., all the population and breeding area were accounted for, 297 records). Species estimates from raw data: In order to control (1) for differences in data quality and/or methods between the different literature sources and (2) for differences in the number of populations found per species, we calculated species estimates (i.e., one estimate per species per variable) for hatching success, adult sex ratio, and breeding density from the raw population-level data. These species-level estimates were obtained as predicted values from models containing one of these variables as response (i.e., separate model was used for each variable), and the variable(s) scoring quality (for hatching success model), season and quality (for adult sex ratio), and methods and quality (for breeding density) as fixed effect factors and species as random effect (following a quantitative genetic approach, but on species instead of individuals, 111). Predicted values were calculated using the MCMCglmm package in R (112), which implements Bayesian generalized linear mixed models with Markov chain Monte Carlo methods. MCMCglmm models were run for 1,000,000 iterations with a burn-in of 1000 iterations and a thinning interval of 500 iterations, with a non-informative prior (V = 1, nu = 0.02, following 112). We checked whether the estimates correlate with the raw species values (expressed as the average of population values) to confirm whether the estimates still contain informative values (Pearson correlations, *P* &lt; 0.001 for all the three estimates with R2 = 0.84, R2 = 0.94, and R2 = 0.87 for hatching success, ASR, and breeding density, respectively).