Sensitivity of Resistance to Net Blotch in Barley

The aim of this study was to demonstrate various methods of analysing terminal net blotch, Pyrenophora teres Drechs. f. teres Smedeg., severity data from 15 spring barleys, Hordeum vulgare L., grown in Finnish official variety trials in five environments. The analyses have been developed and used principally by plant breeders for assessing crop yield, but lend themselves to use by plant pathologists. Pyrenophora teres is the major barley phytopathogen in Finland and improved resistance to it is sought. Joint regression analysis (JRA) and an additive main effects and multiplicative interaction (AMMI) model were used to investigate the data. Statistically significant genotype by environment (GE) interaction for resistance was indicated, and this included qualitative (crossover) interactions among genotypes over environments. A stable, non-sensitive, response to net blotch over environments, combined with a low mean score for terminal severity of the disease characterized the six-row barley 'Thule' which showed statistically significant crossover interaction only with 'Tyra'. 'Kustaa' exhibited the lowest mean terminal net blotch severity, but was relatively sensitive to net blotch. 'Arve' exhibited severe terminal net blotch in all environments, was relatively sensitive to environment and exhibited no crossover interaction with other genotypes. AMMI analysis appeared to represent a useful method for analysing these disease severity data, facilitating the selection of useful sources of resistance. Plots of AMMI-adjusted mean net blotch severities against first principal component axis (PCA) scores were informative for differentiating genotype response over environments, and are therefore potentially useful to plant pathologists and barley breeders seeking to gauge and subsequently improve the resistance status of barley to net blotch.     

Interpreting genotype × environment interaction in tropical maize using linked molecular markers and environmental covariables

An understanding of the genetic and environmental basis of genotype×environment interaction (GEI) is of fundamental importance in plant breeding. In mapping quantitative trait loci (QTLs), suitable genetic populations are grown in different environments causing QTLs×environment interaction (QEI). The main objective of the present study is to show how Partial Least Squares (PLS) regression and Factorial Regression (FR) models using genetic markers and environmental covariables can be used for studying QEI related to GEI. Biomass data were analyzed from a multi-environment trial consisting of 161 lines from a F_3:4 maize segregating population originally created with the purpose of mapping QTLs loci and investigating adaptation differences between highland and lowland tropical maize. PLS and FR methods detected 30 genetic markers (out of 86) that explained a sizeable proportion of the interaction of maize lines over four contrasting environments involving two low-altitude sites, one intermediate-altitude site, and one high-altitude site for biomass production. Based on a previous study, most of the 30 markers were associated with QTLs for biomass and exhibited significant QEI. It was found that marker loci in lines with positive GEI for the highland environments contained more highland alleles, whereas marker loci in lines with positive GEI for intermediate and lowland environments contained more lowland alleles. In addition, PLS and FR models identified maximum temperature as the most-important environmental covariable for GEI. Using a stepwise variable selection procedure, a FR model was constructed for GEI and QEI that exclusively included cross products between genetic markers and environmental covariables. Higher maximum temperature in low- and intermediate-altitude sites affected the expression of some QTLs, while minimum temperature affected the expression of other QTLs. Received: 10 January 1999 / Accepted: 12 March 1999     

Use of the additive main effects and multiplicative interaction model in QTL mapping for adaptation in barley

The additive main effects and multiplicative interaction (AMMI) model has emerged as a powerful analytical tool for genotype x environment studies. The objective of the present study was to assess its value in quantitative trait locus (QTL) mapping. This was done through the analysis of a large two-way table of genotype-by-environment data of barley (Hordeum vulgare L.) grain yields, where the genotypes constituted a genetic population suitable for mapping studies. Grain yield data of 150 doubled haploid lines derived from the Steptoe x Morex cross, and the two parental lines, were taken by the North American Barley Genome Mapping Project (NABGMP) at 16 environments throughout the barley production areas of the USA and Canada. Four regions of the genome were responsible for most of the differential genotypic expression across environments. They accounted for approximately 50% of the genotypic main effect and 30% of the genotype x environment interaction (GE) sums of squares. The magnitude and sign of AMMI scores for genotypes and sites facilitate inferences about specific interactions. The parallel use of classification (cluster analysis of environments) and ordination (principal component analysis of GE matrix) techniques allowed most of the variation present in the genotype x environment matrix to be summarized in just a few dimensions, specifically four QTLs showing differential adaptation to four clusters of environments. Thus, AMMI genotypic scores, when the genotypes constituted a population suitable for QTL mapping, could provide an adequate way of resolving the magnitude and nature of QTL x environment interactions.Ignacio Romagosa was on sabbatical leave from the University of Lleida and the Institut de Recerca i Tecnologia Agroalimentàries, Lleida, Spain, when this study was conducted     

Genetic and nutritional effects on male traits and reproductive performance in Tribolium flour beetles

In Tribolium flour beetles and other organisms, individuals migrate between heterogeneous environments where they often encounter markedly different nutritional conditions. Under these circumstances, theory suggests that genotype-by-environment interactions (GEI) may be important in facilitating adaptation to new environments and maintaining genetic variation for male traits subject to directional selection. Here, we used a nested half-sib breeding design with Tribolium castaneum to partition the separate and joint effects of male genotype and nutritional environment on phenotypic variation in a comprehensive suite of life-history traits, reproductive performance measures across three sequential sexual selection episodes, and fitness. When male genotypes were tested across three nutritional environments, considerable phenotypic plasticity was found for male mating and insemination success, longevity and traits related to larval development. Our results also revealed significant additive genetic variation for male mating rate, sperm offence ability (P(2)), longevity and total fitness and for several traits reflecting both larval and adult resource use. In addition, we found evidence supporting GEI for sperm defence ability (P(1)), adult longevity and larval development; thus, no single male genotype outperforms others in every nutritional environment. These results provide insight into the potential roles of phenotypic plasticity and GEI in facilitating Tribolium adaptation to new environments in ecological and evolutionary time.     

Seedling and adult stage resistance to net form of net blotch (NFNB) in spring barley and stability of adult stage resistance to NFNB in Morocco

This study was conducted to identify stable resistance to net form of net blotch (NFNB) in spring barley in Moroccan environments. Seedling resistance to NFNB was evaluated by inoculating 336 barley genotypes with two NFNB isolates LDNH04Ptt-19 and TD-10 in the greenhouse. These genotypes were evaluated for adult plant resistance to NFNB under seven environments in Morocco in 2015 and 2016. The disease severity was estimated at GS 77–87 on barley leaves using a double-digit scale. To investigate stability of resistance, 149 barley genotypes were subjected to AMMI analysis. At the seedling stage, differential responses of barley genotypes to different NFNB isolates were identified, whereas genotypes had variable stability to NFNB resistance at the adult stages. Five genotypes, AM-68, AM-95, AM-250, AM-267 and AM-322, were resistant to both NFNB isolates at the seedling stage. There were significant (p < .001) effects of genotype (G) and G × E interaction on NFNB severity for barley genotypes at the adult stage. The principal components, IPCA1 and IPCA2, accounted for 48.4% and 18.7% variation for NFNB severity, respectively. The AMMI stability values (ASVs) ranged from 0.01 to 15.5, and fifty-nine barley genotypes had stable responses (ASV ≤ 0.05) across all seven environments. Specifically, two stable genotypes, AM-187 and AM-244, had lower mean NFNB severities across all environments, suggesting a quantitative resistance in these genotypes. Divergent environmental responses of NFNB severity were measured in Sidi El Ayedi 2015 and Sidi Allal Tazi 2016, suggesting that these environments may be suitable to capture resistance to diverse pathotypes. These stable genotypes are valuable resources for introgression of both qualitative resistance and quantitative resistance to NFNB in future.     

Genotype × environment interaction, environmental heterogeneity and the lek paradox

Substantial additive genetic variance (V(A)) often exists for male signalling traits in spite of the directional selection that female choice imposes. One solution to this problem, a conundrum generally termed the 'lek paradox', is that genotype × environment interaction (GEI) occurs and generates a 'crossover' of reaction norms in which no one genotype performs in a superior manner in all environments. Theoretical work indicates that such crossover can sustain genetic variance provided that either (i) spatial heterogeneity in environmental conditions combined with limited migration among populations or (ii) temporal heterogeneity in environmental conditions combined with occasional generation overlap is present. Whereas some recent studies have revealed the intersection of reaction norms for sexually selected traits in laboratory and in natural populations, associated information on environmental heterogeneity, migration and generation overlap has not been investigated. We studied this question in an acoustic pyralid moth, Achroia grisella, in which previous work indicated GEI and crossover of reaction norms for several parameters of the male song evaluated by females. We measured reaction norms for male song as expressed when development was completed under different environmental conditions in four neighbouring, yet isolated, populations during 1 year and in one of these populations during consecutive years. Crossover occurred for the various song parameters in the several populations, but we did not observe a higher incidence of crossover between genotypes taken from two different populations than from the same population. However, for several key song parameters, crossover between genotypes taken from two different years was higher than that between genotypes from the same year. We suggest that temporal heterogeneity in the form of varying selection could potentially conserve V(A) in A. grisella, but we also note other factors that might contribute.     

我国旱地春小麦产量及主要农艺指标的变异分析

采用4年、13个品种(系)、18个试点组成的全国旱地春小麦区域试验产量资料,通过联合方差分析和基因型及其与环境互作（GGE）双标图分析,研究了基因型、环境、基因型与环境互作效应（GEI）对产量变异的影响及品种的产量稳定性.结果表明：环境对产量变异的影响远大于基因型和GEI,环境引起的产量变异占87.5%～92.0%．互作因素中以地点×基因型的互作效应最大,基因型×年份的互作效应最小.我国旱地春小麦基因型多年多点的平均产量水平为2550 kg·hm^-2.产量三要素中,千粒重受环境的影响最小.影响产量变异的主要环境因子有：≥10 ℃年积温、生育期降雨量、平均气温、海拔、年降雨量和无霜期.产量与单位面积穗数（0.675^**）、穗粒数（0.581^**）、千粒重（0.456^**）呈极显著正相关,产量三要素间也呈正相关（0.244～0.480^**）,处于可同步提高范围.     

Genetic variance of sexually selected traits in waxmoths: maintenance by genotype x environment interaction

When traits experience directional selection, such as that imposed by sexual selection, their genetic variance is expected to diminish. Nonetheless, theory and findings from sexual selection predict and demonstrate that male traits favored by female choice retain substantial amounts of additive genetic variance. We explored this dilemma through an ecological genetic approach and focused on the potential contributions of genotype x environment interaction (GEI) to maintenance of additive genetic variance for male signal characters in the lesser waxmoth, Achroia grisella (Lepidoptera: Pyralidae). We artificially selected genetic variants for two male signal characters, signal rate (SR) and peak amplitude (PA), that influence female attraction and then examined the phenotypic plasticity of these variants (high- and low-SR and high- and low-PA lines) under a range of environmental conditions expected in natural populations. Our split-family breeding experiments indicated that two signal characters, SR and PA, and several developmental characters in both high- and low-SR and high- and low-PA lines displayed considerable phenotypic plasticity among the environments tested. Moreover, strong GEIs leading to crossover between high- and low-SR lines were found for SR and developmental period. Therefore, neither high- nor low-SR genetic variants would achieve maximum attractiveness and fitness in every environment, and those variants producing unattractive signals with low SRs under normal conditions may remain in populations provided that gene flow across environments or generation overlap are sufficiently high. We speculate that the phenotypic plasticity for SR and developmental period is adaptive in A. grisella populations experiencing a range of temperature and density conditions. Females mating with attractive (high-SR) males may be assured of obtaining good genes because these males sire offspring that develop more rapidly and a crossover for developmental period may parallel that for SR. Such parallel crossovers may be expected wherever good-genes sexual selection mechanisms operate.     

QTL x environment interactions in rice. I. heading date and plant height

One hundred twenty six doubled-haploid (DH) rice lines were evaluated in nine diverse Asian environments to reveal the genetic basis of genotype × environment interactions (GEI) for plant height (PH) and heading date (HD). A subset of lines was also evaluated in four water-limited environments, where the environmental basis of G × E could be more precisely defined. Responses to the environments were resolved into individual QTL × environment interactions using replicated phenotyping and the mixed linear-model approach. A total of 37 main-effect QTLs and 29 epistatic QTLs were identified. On average, these QTLs were detectable in 56% of the environments. When detected in multiple environments, the main effects of most QTLs were consistent in direction but varied considerably in magnitude across environments. Some QTLs had opposite effects in different environments, particularly in water-limited environments, indicating that they responded to the environments differently. Inconsistent QTL detection across environments was due primarily to non- or weak-expression of the QTL, and in part to significant QTL × environment interaction effects in the opposite direction to QTL main effects, and to pronounced epistasis. QTL × environment interactions were trait- and gene-specific. The greater GEI for HD than for PH in rice were reflected by more environment-specific QTLs, greater frequency and magnitude of QTL × environment interaction effects, and more pronounced epistasis for HD than for PH. Our results demonstrated that QTL × environment interaction is an important property of many QTLs, even for highly heritable traits such as height and maturity. Information about QTL × environment interaction is essential if marker-assisted selection is to be applied to the manipulation of quantitative traits.Communicated by G. Wenzel     

Stability analysis of grain yield in barley (Hordeum vulgare) in the US mid-Atlantic Region

Stability of grain yield performance is an important characteristic in the selection of new crop cultivars. Information from cultivar trials, however, is seldom fully analysed for genotype by environment interactions and, therefore, information on stability of current crop cultivars is lacking. The objectives of this study were to investigate the stability of agronomic traits among genotypes of barley (Hordeum vulgare) across 17 environments (location‐years) in Maryland (USA) from 1994 through 1997 and to examine the effect of locations and years of testing on grain yield performance in this region. Significant differences were observed among barley cultivars and experimental lines for grain yield, plant height, and heading date. Grain yield was positively correlated with plant height and negatively correlated with heading date. Genotype x environment interactions measured through regression analysis were significant for grain yield, heading date and plant height, with the environmental component having the largest effect. Most barley genotypes tested (90%) had regression slopes for grain yield that did not differ from 1.0, indicating good potential for yield response under improving environmental conditions. The most widely grown cultivar in the mid‐Atlantic region, ‘Nomini’, had a regression slope that was higher than 1.0 for grain yield. This indicates that it tends to respond with increasingly higher yields under favorable conditions. In this study, the slope and the standard error of the slope were moderately correlated with grain yield. The genotype's coefficient of variation was not a good indicator of stability for this region. Grain yields of genotype entries common to all years and locations were correlated with corresponding yields at each of the locations and years to assess the relative performance of each location and year. Correlation coefficients across locations were relatively high (r=0.64) within each year of testing. Correlations between years for the same and across locations were generally much lower. The data presented here supports a testing program over more years rather than increased locations to fully characterise the performance of new cultivars.     

Meiotic crossover patterns: Obligatory crossover,interference and homeostasis in a single process

During meiosis, crossover recombination is tightly regulated. A spatial patterning phenomenon known as interference ensures that crossovers are well-spaced along the chromosomes. Additionally, every pair of homologs acquires at least one crossover. A third feature, crossover homeostasis, buffers the system such that the number of crossovers remains steady despite decreases or increases in the number of earlier recombinational interactions. Here we summarize recent work from our laboratory supporting the idea that all 3 of these aspects are intrinsic consequences of a single basic process and suggesting that the underlying logic of this process corresponds to that embodied in a particular (beam-film) model.     

Meiotic crossover patterns: Obligatory crossover,interference and homeostasis in a single process

During meiosis, crossover recombination is tightly regulated. A spatial patterning phenomenon known as interference ensures that crossovers are well-spaced along the chromosomes. Additionally, every pair of homologs acquires at least one crossover. A third feature, crossover homeostasis, buffers the system such that the number of crossovers remains steady despite decreases or increases in the number of earlier recombinational interactions. Here we summarize recent work from our laboratory supporting the idea that all 3 of these aspects are intrinsic consequences of a single basic process and suggesting that the underlying logic of this process corresponds to that embodied in a particular (beam-film) model.     

Genotype-by-genotype interactions modified by a third species in a plant-insect system

Community genetics examines how genotypic variation within a species influences the associated ecological community. The inclusion of additional environmental and genotypic factors is a natural extension of the current community genetics framework. However, the extent to which the presence of and genetic variation in associated species influences interspecific interactions (i.e., genotype x genotype x environment [G x G x E] interactions) has been largely ignored. We used a community genetics approach to study the interaction of barley and aphids in the absence and presence of rhizosphere bacteria. We designed a matrix of aphid genotype and barley genotype combinations and found a significant G x G x E interaction, indicating that the barley-aphid interaction is dependent on the genotypes of the interacting species as well as the biotic environment. We discuss the consequences of the strong G x G x E interaction found in our study in relation to its impact on the study of species interactions in a community context.     

Integration of statistical and physiological analyses of adaptation of near-isogenic barley lines

Seven near-isogenic barley lines, differing for three independent mutant genes, were grown in 15 environments in Spain. Genotype x environment interaction (G x E) for grain yield was examined with the Additive Main Effects and Multiplicative interaction (AMMI) model. The results of this statistical analysis of multilocation yield-data were compared with a morpho-physiological characterization of the lines at two sites (Molina-Cano et al. 1990). The first two principal component axes from the AMMI analysis were strongly associated with the morpho-physiological characters. The independent but parallel discrimination among genotypes reflects genetic differences and highlights the power of the AMMI analysis as a tool to investigate G x E. Characters which appear to be positively associated with yield in the germplasm under study could be identified for some environments.     

Combining genotype, environment and attribute variables in regression models for predicting the cell-means of multi-environment cultivar trials

 The main objectives of this study were: (1) to develop models which combine variables of genotype, environment and attribute in regression models (GEAR) for increasing the accuracy of predicted cell-means of the genotype×environment two-way table, and (2) to compare GEAR models with the additive main effects and multiplicative interaction (AMMI) model. GEAR models were developed by regressing the observed values on principal components of genotypes (PCG) and environments (PCE). Genetic and environmental attributes were also added to the GEAR models. GEAR and AMMI models were applied to multi-environment trials of triticale (trial 1), maize (trial 2) and broad beans (trial 3). The random data-splitting and cross-validation procedure was used and the root mean square-predicted difference (RMSPD) was computed to validate each model. GEAR models increased the accuracy of predicted cell-means. Attribute variables, such as soil pH, rainfall, altitude and class of genotype, did not improve the best GEAR model of trial 1, but they increased the predictive value of other models. Two iterations of the computer program further refined the best GEAR model. Based on the RMSPD criterion, GEAR models were as good as, or better than, some AMMI truncated models for predicting cell-means. The approximate accuracy gain factors (GF) of the best GEAR model over the raw data were 2.08, 3.02 and 2.22, for trials 1, 2 and 3, respectively. The GF of the best AMMI model were 1.74, 2.28 and 2.32 for trials 1, 2 and 3, respectively. The analysis of variance of the predicted cell means showed that the genotype×environment interaction (GEI) variance was reduced by about 20% in trial 1 and 81% in trial 2. A bias associated with the predicted cell reduced the GEI variability. Advantages of using GEAR models in muti-environment cultivar trials are that they: (1) increase the precision of cell-mean estimates and (2) reduce the GEI variance and increase trait heritability. Received: 15 August 1997 / Accepted: 28 October 1997     

QTL and QTL x environment effects on agronomic and nitrogen acquisition traits in rice

Agricultural environments deteriorate due to excess nitrogen application.Breeding for low nitrogen responsive genotypes can reduce soil nitrogen input.Rice genotypes respond variably to soil available nitrogen.The present study attempted quantification of genotype x nitrogen level interaction and mapping of quantitative trait loci (QTLs) associated with nitrogen use efficiency (NUE) and other associated agronomic traits.Twelve parameters were observed across a set of 82 double haploid (DH) lines derived from IR64/Azucena.Three nitrogen regimes namely,native (0 kg/ha; no nitrogen applied),optimum (100 kg/ha) and high (200 kg/ha) replicated thrice were the environments.The parents and DH lines were significantly varying for all traits under different nitrogen regimes.All traits except plant height recorded significant genotype x environment interaction.Individual plant yield was positively correlated with nitrogen use efficiency and nitrogen uptake.Sixteen QTLs were detected by composite interval mapping.Eleven QTLs showed significant QTL x environment interactions.On chromosome 3,seven QTLs were detected associated with nitrogen use,plant yield and associated traits.A QTL region between markers RZ678,RZ574 and RZ284 was associated with nitrogen use and yield.This chromosomal region was enriched with expressed gene sequences of known key nitrogen assimilation genes.     

Limitations of conventional regression analysis a proposed modification

Summary The conventional genotype-environment interaction analysis cannot detect the theoretically ideal genotype which has been defined as the one with relatively low sensitivity in the poor environments and high sensitivity in the favourable environments. The computation of separate regression coefficients on the two regions of the response curve has been suggested to detect such genotypes. This procedure is simple and more convenient than the complicated curvilinear regression analysis.     

Alternative partitioning of the genotype-by-environment interaction

Summary Alternative methods for partitioning the genotype-by-environment interaction, for an arbitrary number of genotypes or environments, were examined. Partitioning of the interaction is important in order to determine the nature of the interaction. Two methods of partitioning were examined; both separated the interaction into two types: (1) due to heterogeneous variances or (2) due to imperfect correlations. Method 1 was based on heterogeneity among environments in the scaling of differences among genotypes. Method 2 was based on heterogeneity among genotypes in the scaling of differences among environments. Any remaining interaction arises from deviations from the perfect positive correlation of genotypic rankings among environments (Method 1) or of environmental rankings among genotypes (Method 2). Method 1 is more appropriate for random genotypes that are to be tested in either fixed or random environments. With Method 1, the interactions that arise mainly from heterogeneity of genotypic scaling among environments are generally unimportant. However, if environments are fixed and interactions are mainly due to imperfect correlations of rankings, specialized lines may be indicated for each environment. Method 2 is more useful in evaluating fixed genotypes for sensitivity to random environments. A partitioning of the interaction into that due to the type of interaction within each genotype was shown to be useful in that situation.Journal Paper No. 123737 of the Purdue University Agricultural Experiment Station     

Crop diagnosis and probe genotypes for interpreting genotype environment interaction in winter wheat trials

Genotype*environment interaction has been analyzed with 12 genotypes and four probe genotypes in French wheat trials. An integrated approach was developed which combined crop diagnosis with the analysis of interaction by factorial regression. Crop diagnosis was helpful to characterize the environments and to select environmental variables. Such an approach succeeded in providing an agronomic explanation of genotype*environment interaction and in defining the responses or parameters for each genotype and each environment. Earliness at heading, susceptibility to powdery mildew and susceptibility to lodging were the three major genotypic covariates. Interaction could also be related to environment features, measured indirectly by the behavior of the four probe genotypes during the formation of yield, what we called the outputs of a simplified crop diagnosis, or described directly by indicators of yield-limiting factors. Two important crop diagnosis covariates were analyzed in order to characterize interaction during the formation of yield: the reduction in kernel number, which described the time-period until flowering, and the reduction in thousand kernel weight, which corresponded to the period after flowering. These variates were estimated for each probe genotype and allowed us to compare the behavior of the 12 genotypes to that of the probe genotypes. Both periods of the formation of yield contributed to the interaction, and ’Camp-Rémy’ was the probe of particular interest for the comparisons. When true environmental variates were used, factorial regression revealed that water deficits during the formation of grain number and level of nitrogen were predominant. Such an integrated approach could be exploited when varieties are tested in a network where numerous and diverse yield-limiting factors may occur. Received: 3 August 1998 / Accepted: 16 March 1999     

Sex-specific genotype-by-environment interactions for cuticular hydrocarbon expression in decorated crickets, Gryllodes sigillatus: implications for the evolution of signal reliability

Phenotypic traits that convey information about individual identity or quality are important in animal social interactions, and the degree to which such traits are influenced by environmental variation can have profound effects on the reliability of these cues. Using inbred genetic lines of the decorated cricket, Gryllodes sigillatus, we manipulated diet quality to test how the cuticular hydrocarbon (CHC) profiles of males and females respond across two different nutritional rearing environments. There were significant differences between lines in the CHC profiles of females, but the effect of diet was not quite statistically significant. There was no significant genotype-by-environment interaction (GEI), suggesting that environmental effects on phenotypic variation in female CHCs are independent of genotype. There was, however, a significant effect of GEI for males, with changes in both signal quantity and content, suggesting that environmental effects on phenotypic expression of male CHCs are dependent on genotype. The differential response of male and female CHC expression to variation in the nutritional environment suggests that these chemical cues may be under sex-specific selection for signal reliability. Female CHCs show the characteristics of reliable cues of identity: high genetic variability, low condition dependence and a high degree of genetic determination. This supports earlier work showing that female CHCs are used in self-recognition to identify previous mates and facilitate polyandry. In contrast, male CHCs show the characteristics of reliable cues of quality: condition dependence and a relatively higher degree of environmental determination. This suggests that male CHCs are likely to function as cues of underlying quality during mate choice and/or male dominance interactions.