DOI: 10.5061/dryad.mkkwh712j
title: Effects of genetic vs. environmental quality on condition-dependent morphological and life history traits in a neriid fly

description: Condition is assumed to reflect both genes and environment, enabling
 condition-dependent signals to reveal genetic quality. However, because
 the phenotypic effects of variation in genetic quality could be masked by
 environmental heterogeneity, the contribution of genetic quality to
 phenotypic variation in fitness-related traits and condition-dependent
 signals remains unclear. We compared effects of ecologically relevant
 manipulations of environmental quality (nutrient dilution in the larval
 diet) and genetic quality (one generation of inbreeding) on male and
 female morphology, life history and reproductive performance in the neriid
 fly Telostylinus angusticollis. We found that larval diet quality had
 strong, positive effects on male and female body size, male secondary
 sexual traits, and aspects of male and female reproductive performance. By
 contrast, inbreeding had weak effects on most traits, and no trait showed
 clear and consistent effects of both environmental and genetic quality.
 Indeed, inbreeding effects on body size and male competitive performance
 were of opposite sign in rich vs. poor larval diet treatment groups. Our
 results suggest that environmental quality strongly affects condition, but
 the effects of genetic quality are subtle and environment-dependent in
 this species. These findings raise questions about the genetic
 architecture of condition and the potential for condition-dependent traits
 to function as signals of genetic quality.
description: <strong>Experimental setup</strong>
 Lab stocks used for this experiment were established with
 individuals collected from a naturally occurring population in Flat Rock
 Gully Reserve in Sydney, Australia (33°49'02.6"S
 151°12'32.0"E) approximately 10 generations prior to the
 experiment and maintained as a large outbred population with overlapping
 generations. In stock cages, females oviposited on the same batch of
 larval medium over several days and larvae thus experienced a range of
 nutritional conditions, preventing adaptation to a particular nutrient
 concentration. To ensure high genetic diversity, stocks were supplemented
 with animals collected from the same natural population one generation
 prior to the experiment. To create high and low genetic
 quality treatment groups while also controlling for genotype, we created
 inbred and outbred families in a genetic block design (Fox & Reed,
 2011, Roff, 1998). To create genetic blocks, unmated males and females
 from the stock population were randomly paired to create full sibling
 families. Twenty eggs from each pair were transferred to 100g of
 “intermediate” larval medium consisting of 10.9g protein (Nature’s Way soy
 protein isolate; Pharm-a-Care, Warriewood, Australia) and 29.7g
 carbohydrate (brown sugar; Coles brand, Bundaberg, Australia) per 500mL
 water and 1L of cocopeat. Two full sibling families (F0) were randomly
 paired to create a genetic block, and crosses were set up within and
 between families within each genetic block so as to create two inbred and
 two outbred broods per genetic block (Fig. 2). We
 manipulated larval diet (environmental quality) in a split brood design
 (Fig. 2). From each brood within each genetic block, 20 eggs were
 transferred to 100g of nutrient-rich (“rich”) larval diet medium, and 20
 eggs were transferred to 100g of nutrient-poor (“poor”) larval diet
 medium, representing high- and low-quality environments, respectively. The
 rich larval medium consisted of 32.8g soy protein and 89g of brown sugar
 per 500 mL of reverse osmosis water and 1L of cocopeat. The poor larval
 medium consisted of 5.5g soy protein and 14.8g brown sugar for the same
 quantity of water and cocopeat. Upon eclosion,
 treatment flies (F1) were transferred to same sex full sibling groups of
 standardised density until sexual maturity was reached two weeks after
 eclosion (very little mortality occurred during this period).  At this
 point, a single individual of each sex from each family was randomly
 selected for the reproductive assays (i.e., eight females and eight males
 from each genetic block). From each F1 full-sibling brood, five additional
 flies of each sex (where possible) were randomly selected and photographed
 for morphology analysis (see below). This design resulted in a total of
 543 F1 individuals for reproductive assays, and an additional 2,061 F1
 individuals for morphology analysis from 35 genetic blocks. This
 experiment was carried out in two temporal blocks, with 19 genetic blocks
 in the first temporal block and 16 in the second. Temporal blocks were set
 up two weeks apart using the same lab population, with each temporal block
 comprising a distinct set of genetic blocks.
 <strong>Non-competitive reproductive performance
 assay</strong> Flies were placed individually in
 a scintillation vial with an unmated partner fly of the opposite sex.
 Partner flies were reared on an intermediate quality larval diet, and were
 two weeks old at time of pairing. The pair were left to interact for one
 hour, and during this time we recorded latency to first mating and total
 number of matings that occurred. Mating occurred in 173 of 282 pairs
 (63%), and each mated female was provided with an oviposition dish to lay
 eggs for 96 hours. The dish was checked after 48 and 96 hours, all eggs
 were tallied, and 20 eggs were transferred to 100g of intermediate larval
 medium and incubated at 25°C. Ten days after eclosion of the first
 offspring (F2), the total number of adults was recorded to assess
 egg-to-adult viability. Although mating outcome depends on the features
 and behaviour of both partners, we interpret latency to mating and mating
 success with standardized partners as at least partly indicative of the
 average attractiveness and/or vigour of the focal individual. A female’s
 larval diet or inbreeding status could affect her ability to provision her
 eggs. Similarly, a male’s larval diet or inbreeding status could affect
 the quality of his offspring by modulating the nongenetic factors that
 mediate paternal effects (Crean et al., 2016, Crean &
 Bonduriansky, 2014). Treatment effects on female fecundity or offspring
 performance can reflect direct effects of the focal individual (e.g.
 female reproductive investment, or male investment in accessory gland
 proteins that affect oviposition or offspring development), or
 differential allocation by its partner.
 <strong>Male competitive performance
 assay</strong> As performance in combat is likely
 to be a major determinant of male fitness and is affected by larval diet
 quality in this species (Hooper et al., 2017), we measured male-male
 combat success and competitive mating success in treatment males.
 Treatment males were placed in a 250mL container with a competitor male
 and a female (both from separate outbred stocks and reared on intermediate
 quality diets). To distinguish the two males, competitor males’ food was
 mixed with blue food dye for two days before this assay, causing their
 abdomens to turn a bright blue colour. The two males were placed in the
 container together for 12 hours to establish dominance hierarchies (see
 Bonduriansky & Head, 2007), and the female was then introduced.
 The trio was observed for one hour, and during this time we recorded the
 total number of matings that occurred and how many were performed by the
 treatment male. We also recorded male-male interactions, which we
 classified as fully escalated combat (involving a characteristic vertical
 contact posture; (Hooper et al., 2017)), or a non-fully escalated contest
 (where physical contact occurred but without the vertical posture). We
 also recorded which individual initiated the interaction (i.e., was the
 first to orient, raise its body and move towards its rival), and which
 individual “lost” (i.e., retreated, typically turning and moving &gt;
 1 body length away from its rival).
 <strong>Lifespan and morphology</strong>
 Following the reproductive assay, flies were housed individually
 in 250mL cages provided with sugar and yeast as a food source, and ad
 libitum access to water. These cages were monitored every other day to
 record any deaths. After death, treatment flies were photographed for
 morphology analysis using a Leica DFC420 digital camera mounted on Leica
 MS5 microscope. From these photos, ImageJ software (National Institutes of
 Health, Bethesda, Maryland, USA) was used to measure forelimb femur
 length, forelimb tibia length, midlimb femur length, midlimb tibia length,
 head length, head width, and thorax length, antenna length, and wing
 length (quantified as the length of the R4+5 vein from the r-m cross vein
 to the wing margin) (Supplementary materials, Fig. S1). Where possible,
 both left and right appendages were measured and the average of the two
 was used for analysis. <strong>Statistical
 analysis</strong> Model fitting was carried out
 in R version 3.3.2 (R_Development_Core_Team, 2008). Unless noted
 otherwise, models included larval diet, inbreeding treatment, sex (where
 appropriate), two and three-way interactions among these, and temporal
 block as fixed effects, and genetic block (uniquely numbered) as a random
 effect. Linear mixed effects models were fitted using the package lme4
 (Bates et al., 2015). We tested effects in Gaussian models using
 Satterthwaite F-tests from the lmerTest package (Kuznetsova et al., 2017);
 simulations show that these tests are more reliable than likelihood-ratio
 tests when sample sizes are modest (Luke, 2017). Statistical results from
 models are reported in the text as the effect coefficient (b) +/- its
 standard error (SE), and associated P-value. We do not correct for
 multiple testing because we base our conclusions on the overall pattern of
 results across all traits. PCA on all morphological
 traits (carried out on the correlation matrix separately for each sex)
 showed that all traits loaded strongly on PC1 in both sexes (Supplementary
 Material, Tables S1, S2). PC1 scores were therefore used as an index of
 body size for each sex. In addition, because thorax length is often used
 as an index of body size in this species and in other Diptera
 (Bonduriansky, 2006), we also analysed variation in thorax length. Body
 size strongly influences dominance in males and fecundity in females
 (Bonduriansky & Head, 2007). The lsmeans package (Lenth, 2016) was
 used to carry out multiple comparisons. T. angusticollis exhibits highly
 sexually dimorphic body shape when reared on a nutrient-rich larval diet
 (Bonduriansky, 2007), and male body shape influences performance in sexual
 interactions (Fricke et al., 2015). To investigate treatment effects on
 body shape in males, we used PC2 and PC3 scores as body size-independent
 indexes of body shape variation (see Results). Note that, because body
 shape is strongly correlated with body size in T. angusticollis males
 (Bonduriansky, 2007), PC2 and PC3 explain small fractions of overall
 morphological variance (see Results). However, these components represent
 important vectors of body shape variation and appear to influence male
 performance (e.g. see Fricke et al., 2015). Female body shape was not
 analysed because the functional consequences (if any) of variation in
 female body shape are unknown. Mortality rate of
 treatment individuals was analysed using Cox proportional hazard
 regression using the coxme package. Interactions were tested with
 likelihood ratio tests. Thorax length, PC1, PC2 and PC3
 scores, development time (egg to adult) of the focal (F1) individuals, and
 latency to first mating were analysed using Gaussian models (separately
 for each sex, unless otherwise indicated). Probability of mating at least
 once was analysed with a generalised linear mixed effects model with
 binomial error structure. Number of matings achieved during the assay, as
 well as the number of eggs laid after the pairing, were both analysed with
 a generalised linear mixed effects model with Poisson error structure. The
 number of matings during the assay was included as a covariate in the
 analysis of number of eggs laid because amount of ejaculate transferred
 can affect oviposition rate. Egg-to-adult viability of F1 broods and their
 F2 offspring was analysed with a generalised linear mixed effects model as
 a matrix of successes and failures with binomial error structure.
 Additionally, in the models for number of eggs laid, and egg-to-adult
 viability of those eggs, an observation-level random effect was included
 to correct for overdispersion. For the competitive assay, proportion of
 matings by the focal male was analysed as a binomial matrix of successes
 and failures using a generalised linear mixed effects model.
 To reduce the dimensionality of the combat performance data, we
 carried out a PCA of all the competitive behaviours. This analysis
 suggested that the proportion of contests “won” by the focal male is the
 single trait that best encapsulates variation in combat performance
 (Supplementary Material, Fig. S3, Table S8). We therefore analysed the
 proportion of contests won as a matrix of successes and failures in a
 generalised linear mixed effects model with binomial errors, and including
 an observation-level random effect to correct for
 overdispersion.
description: Please see README files for explanation of variables and missing
 values.