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.

Experimental setup

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.

Non-competitive reproductive performance assay

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.

Male competitive performance assay

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 > 1 body length away from its rival).

Lifespan and morphology

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.

Statistical analysis

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.

Please see README files for explanation of variables and missing values.