DOI: 10.5061/dryad.pzgmsbcrz
title: Variance in offspring sex ratio and maternal allocation in a highly invasive mammal

description: Skewed sex ratios at birth are widely reported in wild populations,
 however the extent to which parents are able to modulate the sex ratio of
 offspring to maximize their own fitness remains unclear. This is
 particularly true for highly polytocous species as maximizing fitness may
 include trade-offs between sex ratio and the size and number of offspring
 in litters. In such cases, it may be adaptive for mothers to adjust both
 the number of offspring per litter and offspring sex to maximize
 individual fitness. Investigating maternal sex allocation in wild pigs
 (Sus scrofa) under stochastic environmental conditions, we predicted that,
 under favorable conditions, high quality mothers (larger, older) would
 produce male-biased litters and invest more in producing larger litters
 with more males. We also predicted sex ratio would vary relative to litter
 size, with a male-bias among smaller litters. We found evidence that
 increasing wild boar ancestry, maternal age and condition, and resource
 availability may weakly contribute to male-biased sex ratio, however,
 unknown factors not measured in this study are assumed to be more
 influential. High quality mothers allocated more resources in litter
 production, but this relationship was driven by adjustment of litter size,
 not sex ratio. There was no relationship between sex ratio and litter
 size. Collectively, our results emphasized that adjustment of litter size
 appeared to be the primary reproductive characteristic manipulated in wild
 pigs to increase fitness rather than adjustment of offspring sex ratio.
description: This study was conducted at the Savannah River Site (SRS), a
 78,000 ha U.S. Department of Energy facility located in Aiken, Barnwell,
 and Allendale counties, South Carolina, USA. We sampled from live-trapped
 (and consequently released for other studies, e.g., neonate survival
 [Chinn et al. 2021]) and humanely-euthanized according to established
 protocols (A2015 12-017) wild pigs throughout the year between March 2017
 and July 2019. We collected fetal data, tissue for genetic analysis, and
 morphological measurements from females &gt;27 kg to quantify litter
 and maternal attributes (n = 160). We weighed and measured each female
 dorsally from snout to base of tail. We calculated a standardized body
 condition index (subsequently referred to as maternal condition) for each
 individual as mass/length (LaBocha et al., 2014). We measured extraneous
 fat reserves, a quantitative measurement of maternal nutritional
 condition, from culled females and used it as a proxy for local resource
 availability. We assessed age by tooth eruption and replacement patterns
 (Matschke, 1967; Mayer, 2002), and individuals were classified into 3 age
 classes: juvenile (between 6 months and 1 year), yearling (1-1.5 years),
 and adults (≥ 1.5 years old). If present, fetuses were removed, weighed
 and measured in a straight-line from crown to rump (CRL). Fetuses ≥36 days
 old were sufficiently developed to visually determine sex. We quantified
 the ancestry of wild pigs following methods described in Smyser et al.
 (2020).  We centered and z-transformed continuous
 variables to a mean of 0 and a standard deviation of 1 to allow for
 standardized comparison for all analyses. We censored individuals from
 analyses if they did not have all variables measured (i.e., removed a
 female from analysis if she was missing rump fat data). 
description: All analyses were performed in R 4.0.5 (R Core Team, 2021). We
 used package lme4 (Bates et al. 2015) for some analyses.
description: # Chinn et al. 2023 Variance in offspring sex ratio and maternal
 allocation in a highly invasive mammal
 [https://doi.org/10.5061/dryad.pzgmsbcrz](https://doi.org/10.5061/dryad.pzgmsbcrz) Manuscript citation: Chinn, S. M., Smyser, T., & Beasley, J. C. (2023). Variance in offspring sex ratio and maternal allocation in a highly invasive mammal. *Ecology and Evolution*, *13*(5), e10136. \## Corresponding author: Dr. Sarah M. Chinn, [sarahchinn@gmail.com](mailto:sarahchinn@gmail.com) These are original data for the manuscript published in Ecology and Evolution. This file explains all variables in the dataset that accompany Chinn et al. 2023 (Ecology and Evolution). For data not collected for a specific variable are represented by 'NA' in the datasets. ## Description of the data and file structure \# 1. Dataset: Chinn.et.al.2023_SexRatioData.csv Analyses: Sex Ratio Triver-Willard (GLM), Allocation Williams (LM), Fig5a Allocation vs boar ancestry, Fig5b Allocation vs maternal condition, Summary stats for litter size, Fig6 Average sex ratio by litter size (figure) sow: individual female sampled (n=89) age: age class of sow yr: age in years (aged by Matson lab, tooth cementum) year: year sow sampled (2017-2019) males: # of male fetuses/offspring in litter females: # of female fetuses/offspring in litter litterno: litter size sexratio: litter sex ratio - # males/(# males + # females) allocation: maternal allocation in litter = # males * cost of producing a male + # females * cost of producing a female ``` Ex: males are 2% greater in mass compared to female fetuses Cost of male = 1.02*cost of female, when cost of female=1 litter has 2 males + 3 females. Allocation = 2*1.02 + 3*1 = 5.04 ``` size: maternal condition index - mass/length fat: scaled rump fat values littersize: scaled litter size fetusmass: scaled average fetus mass rumpfat: raw rump fat values boar: scaled % wild boar ancestry size_raw: raw maternal condition index values boar_raw: raw % wild boar ancestry \# 2. Dataset: Chinn.et.al.2023_Fat_2017.csv, Chinn.et.al.2023_Fat_2018.csv, Chinn.et.al.2023_Fat_2019.csv Analyses: Rump fat summary (mean + sd for each year) sow: ID of individual female sampled year: year sow was sampled rumpfat: raw measure of rump fat (cm) \# 3. Dataset: Chinn.et.al.2023_AllRumpFat.csv Analysis: ANOVA to determine if there were differences in rump fat by year for all sows in study, n=514 (some missing data) sow: ID of individual female sampled year: year sow was sampled rumpfat: raw measure of rump fat (cm) \# 4.Dataset: Chinn.et.al.2023_PregnantRumpFat.csv Analysis: ANOVA to determine if there were difference sin rump fat by year for only pregnant sows, n=155 (some missing data) sow: ID of individual female sampled repro: reproductive status (all females in this data set are pregnant) year: year sow was sampled rumpfat: raw measure of rump fat (cm) \# 5. Dataset: Chinn.et.al.2023_MassAge.csv Analyses: Determine if there were differences in fetal mass by age- Fig2; Difference in sex ratio of fetal litters by fetal age- Fig4; Determine if fetal mass changed over time by sex- Fig3 sow: individual female sampled (n=89) sexratio: litter sex ratio - # males/(# males + # females) CRL: mean crown-rump length for the litter henrydays: age (days) of litter based on CRL predictedageR: predicted age (days) of litter using regression to fill in gaps that Henry could not estimate (smaller CRL values) LitterMass: mean litter mass (all males and females in a litter) littersize: litter size (number of offspring) maleMass: mean mass of all male offspring males: # of males in litter femaleMass: mean mass of all female offspring females: # of females in litter male-female: value of the mean mass of males-mean mass of females